ci: bump version with Build-160

fix(bot): seed search with game history, add contempt and NNUE mop-up
Repetition: alpha-beta seeded the repetition map with only the root position, so search was blind to positions already reached in the real game and would happily shuffle into draws when ahead. Reconstruct the full game-history position hashes by replaying moves and seed the search state with them; treat a twofold occurrence at non-root nodes as a draw. Contempt: draws are now scored CONTEMPT (25cp) away from zero, signed by ply parity, so the bot avoids dead-equal repetitions instead of settling. Endgame: pure NNUE lacks mating knowledge and stalls KX-vs-K conversions. Add a MopUp correction (edge-driving + king-proximity) applied only in lone-king endgames with sufficient mating material; zero elsewhere so middlegame NNUE output is untouched. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-30 10:21:06 +00:00 · 2026-06-30 12:04:27 +02:00 · 2026-06-29 17:34:14 +00:00 · 2026-06-29 19:18:31 +02:00 · 2026-06-24 20:41:25 +00:00 · 2026-06-24 22:28:53 +02:00
9 changed files with 386 additions and 52 deletions
@@ -1146,3 +1146,174 @@
 ### Reverts

 * Revert "refactor: update metrics paths formatting in application.yml for clarity" ([3870566](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/38705663498d5f47c40dafe2f26198589ede8656))
+##  (2026-06-24)
+
+### Features
+
+* add initialization metrics for various services ([d438e97](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/d438e97f32bdde0bfc63c1b4a8cc810cdd093166))
+* add OpenTelemetry trace configuration with parentbased sampler ([3904d5a](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/3904d5ad8ad4930ddee65287a7bfab785a6148f5))
+* **analytics:** add Spark batch analytics module ([#70](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/70)) ([39f1657](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/39f1657e1db6e84889af338c43be8cb5c03c3ec3))
+* **config:** update application.yml for PostgreSQL and remove staging/production configurations ([2404e61](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/2404e6164c3b50ffccbea5238d636060d6abe4d6))
+* **config:** update application.yml for staging and production environments ([6113432](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/6113432a14c476a3a0dfc0d449e17d023697f2ba))
+* configure logging and add OpenTelemetry support ([#49](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/49)) ([d57c488](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/d57c4886612d1d92da0e1b79209fc83e6ef537a1))
+* **docker:** add .dockerignore and .gitignore files for build exclusions ([c987d8e](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/c987d8e258c0e6c4cfbdaa8381c64c410d7a2b83))
+* **docker:** add Dockerfiles for building Quarkus application in native and JVM modes ([3f2d2bb](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/3f2d2bb4c97fa8cddba66e1da4427c54236dfeed))
+* **docker:** add Dockerfiles for Quarkus application in JVM and native modes ([34b9933](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/34b993304670cf2aa62cd2f6460cee7b9864b08e))
+* **events:** migrate game-creation and bot flows to Redis Streams NCS-89 ([#62](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/62)) ([a24924c](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/a24924c23057db3d700a75dbc4333557789cd991))
+* **ncs-110:** feed NNUE root-move scores into search move ordering ([#83](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/83)) ([e4fee85](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/e4fee8513430093d46957970618935e99591519f))
+* NCS-78 Add Traceability to the Applications ([#46](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/46)) ([649566e](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/649566eb3fcf38f91c8896a739f74ea318af312d))
+* NCS-78 Add Traceability to the Applications ([#47](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/47)) ([87dfc6c](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/87dfc6c2bcce7f7d58fc641bd8d468a2e584c108))
+* NCS-82 add Swiss-system tournament module ([#55](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/55)) ([c5661de](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/c5661de4a0ebf4b33211f5a391840dcf744656b7))
+* **official-bots:** activate opening book in expert bot (native-safe) ([260db25](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/260db25803ec55ce99e55782791eabdc190dfed4))
+* **official-bots:** add Google Colab notebook for NNUE training (NCS-111) ([#81](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/81)) ([fa10852](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/fa10852bc98451d4068ec6fb9e7a486b5e53ef5c))
+* **official-bots:** consume GameOver stream for bot cleanup ([#67](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/67)) ([db9d153](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/db9d1533912f4b41c4d1ca80ccffdde5d23d6ff6))
+* **official-bots:** implement king-relative (HalfKP) encoding in NNUE (NCS-109) ([#80](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/80)) ([44f376f](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/44f376f03221f086b898741436e13c93fd314dd1))
+* **official-bots:** make HybridBot veto actionable and use it for expert ([1df29cf](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/1df29cf3a6e21af3f396b2b7a6da67d978f941ae))
+* **official-bots:** park expert bot on tournament server at startup ([#75](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/75)) ([30295a4](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/30295a4bb95855ee8261c92278bb9ebc80ee12ee))
+* **official-bots:** resolve tournament bot token from Redis and account service ([386ddc5](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/386ddc5c19f8f893b16c6422aa5393b54c872e45))
+* **official-bots:** standalone self-play + one-shot dataset builder for NNUE training ([1c80abd](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/1c80abdb8a45814d642d43c633cde81ce7374c4f))
+* **tournament:** auto-join external tournaments and publish created ones ([#77](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/77)) ([9978b7e](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/9978b7ea78eb658a225a461b9cd339386c0c14f3))
+* **tournament:** federate tournaments across clusters with DB replication ([5b000a6](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/5b000a6e5f04ea6770d1c7ab6bfdaded77a99172))
+* **tournament:** seed external server registry from env var on startup ([845dc9c](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/845dc9c2935c8bc1be42541dfaf31c9a861d3272))
+* true-microservices ([#40](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/40)) ([5909242](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/590924254e8a2754de661a57a03e43f89ceb6299))
+
+### Bug Fixes
+
+* enable official bots to connect to external tournament server ([#71](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/71)) ([688d30e](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/688d30e2b10026923372be5fca3c63eaaee2de2a))
+* modified training pipeline ([9f9140c](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/9f9140cb585345cd244a1dfee1a06e51a5f7f7a8))
+* **official-bots:** configure JWT verification ([#72](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/72)) ([98c64fc](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/98c64fc0d56dc542beb31c75f4b9056d91de03cd))
+* **official-bots:** correct parkOn path from /api/bots to /api/account/bots ([1be9949](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/1be9949c0b5c6a1db535696620d77735050d6c93))
+* **official-bots:** derive tournament game color from game endpoint ([#79](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/79)) ([bfc4672](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/bfc46723e615bb9b65f7f9bba5f53877c4f079a7))
+* **official-bots:** discover tournament games by polling, not just the stream ([10113fd](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/10113fd0579b614d15870798d933bc9c495d2049))
+* **official-bots:** make botToken optional, fall back to env, fix 502 status ([f43d193](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/f43d1930d80670d810c57b54eaa3789854fa082c))
+* **official-bots:** NCS-70-auto-register official bots with account service ([#59](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/59)) ([7117a93](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/7117a93376272094d0b1a6abf2121254ce396684))
+* **official-bots:** park on external tournament servers using correct endpoint and token ([3188241](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/31882417377468b41bbe3ff94506aa4928024450))
+* **official-bots:** play games by polling state instead of NDJSON stream ([bfb15c7](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/bfb15c7299bd471d5e064a577ed10af98e2ea90a))
+* **official-bots:** play only own tournament games with correct color ([4651bb7](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/4651bb796f07a21bd013d9521b2dfe2e1078cebb))
+* **official-bots:** prevent Colab OOM in NNUE training ([e2b4342](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/e2b4342f602215b5e8de6fccafc4105525a1ddd1))
+* **official-bots:** prioritize Redis token over stale env var in joinTournament ([83dd2d4](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/83dd2d4335ca48eb3e5aa234a75367574276ba63))
+* **official-bots:** register with tournament server directly to get correct token ([64b5d55](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/64b5d5567f110c2fe152558c7de275a1e0b30e21))
+* **official-bots:** resolve per-difficulty bot token on tournament join ([fdf4c94](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/fdf4c94811d086996447bb4657fac1d9bd6e5a93))
+* **official-bots:** resume tournaments already joined after restart ([285b73e](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/285b73efbd6dd98cec410ade9eead9881d693a8f))
+* **official-bots:** stream NNUE features as sparse indices to stop host OOM ([9d65662](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/9d656624d85889f55746faa5704578e248f9b088))
+* **official-bots:** sync bots before token fetch on first startup after DB wipe ([b0ddb27](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/b0ddb274d23bca8b1b3f691ce0d643f33e0b54cd))
+* **official-bots:** use ThreadLocalRandom in PolyglotBook for native image ([1b30c3b](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/1b30c3be393d25712c8743d3d9057207f8bbb67c))
+
+### Reverts
+
+* Revert "refactor: update metrics paths formatting in application.yml for clarity" ([3870566](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/38705663498d5f47c40dafe2f26198589ede8656))
+##  (2026-06-29)
+
+### Features
+
+* add initialization metrics for various services ([d438e97](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/d438e97f32bdde0bfc63c1b4a8cc810cdd093166))
+* add OpenTelemetry trace configuration with parentbased sampler ([3904d5a](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/3904d5ad8ad4930ddee65287a7bfab785a6148f5))
+* **analytics:** add Spark batch analytics module ([#70](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/70)) ([39f1657](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/39f1657e1db6e84889af338c43be8cb5c03c3ec3))
+* **config:** update application.yml for PostgreSQL and remove staging/production configurations ([2404e61](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/2404e6164c3b50ffccbea5238d636060d6abe4d6))
+* **config:** update application.yml for staging and production environments ([6113432](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/6113432a14c476a3a0dfc0d449e17d023697f2ba))
+* configure logging and add OpenTelemetry support ([#49](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/49)) ([d57c488](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/d57c4886612d1d92da0e1b79209fc83e6ef537a1))
+* **docker:** add .dockerignore and .gitignore files for build exclusions ([c987d8e](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/c987d8e258c0e6c4cfbdaa8381c64c410d7a2b83))
+* **docker:** add Dockerfiles for building Quarkus application in native and JVM modes ([3f2d2bb](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/3f2d2bb4c97fa8cddba66e1da4427c54236dfeed))
+* **docker:** add Dockerfiles for Quarkus application in JVM and native modes ([34b9933](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/34b993304670cf2aa62cd2f6460cee7b9864b08e))
+* **events:** migrate game-creation and bot flows to Redis Streams NCS-89 ([#62](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/62)) ([a24924c](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/a24924c23057db3d700a75dbc4333557789cd991))
+* **ncs-110:** feed NNUE root-move scores into search move ordering ([#83](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/83)) ([e4fee85](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/e4fee8513430093d46957970618935e99591519f))
+* NCS-78 Add Traceability to the Applications ([#46](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/46)) ([649566e](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/649566eb3fcf38f91c8896a739f74ea318af312d))
+* NCS-78 Add Traceability to the Applications ([#47](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/47)) ([87dfc6c](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/87dfc6c2bcce7f7d58fc641bd8d468a2e584c108))
+* NCS-82 add Swiss-system tournament module ([#55](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/55)) ([c5661de](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/c5661de4a0ebf4b33211f5a391840dcf744656b7))
+* **official-bots:** activate opening book in expert bot (native-safe) ([260db25](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/260db25803ec55ce99e55782791eabdc190dfed4))
+* **official-bots:** add Google Colab notebook for NNUE training (NCS-111) ([#81](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/81)) ([fa10852](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/fa10852bc98451d4068ec6fb9e7a486b5e53ef5c))
+* **official-bots:** consume GameOver stream for bot cleanup ([#67](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/67)) ([db9d153](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/db9d1533912f4b41c4d1ca80ccffdde5d23d6ff6))
+* **official-bots:** implement king-relative (HalfKP) encoding in NNUE (NCS-109) ([#80](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/80)) ([44f376f](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/44f376f03221f086b898741436e13c93fd314dd1))
+* **official-bots:** make HybridBot veto actionable and use it for expert ([1df29cf](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/1df29cf3a6e21af3f396b2b7a6da67d978f941ae))
+* **official-bots:** park expert bot on tournament server at startup ([#75](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/75)) ([30295a4](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/30295a4bb95855ee8261c92278bb9ebc80ee12ee))
+* **official-bots:** resolve tournament bot token from Redis and account service ([386ddc5](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/386ddc5c19f8f893b16c6422aa5393b54c872e45))
+* **official-bots:** standalone self-play + one-shot dataset builder for NNUE training ([1c80abd](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/1c80abdb8a45814d642d43c633cde81ce7374c4f))
+* **tournament:** auto-join external tournaments and publish created ones ([#77](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/77)) ([9978b7e](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/9978b7ea78eb658a225a461b9cd339386c0c14f3))
+* **tournament:** federate tournaments across clusters with DB replication ([5b000a6](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/5b000a6e5f04ea6770d1c7ab6bfdaded77a99172))
+* **tournament:** seed external server registry from env var on startup ([845dc9c](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/845dc9c2935c8bc1be42541dfaf31c9a861d3272))
+* true-microservices ([#40](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/40)) ([5909242](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/590924254e8a2754de661a57a03e43f89ceb6299))
+
+### Bug Fixes
+
+* **bot:** include quiet promotions in quiescence search ([4938560](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/49385600147021cd29f00a8eecc6be7ba8470717))
+* enable official bots to connect to external tournament server ([#71](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/71)) ([688d30e](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/688d30e2b10026923372be5fca3c63eaaee2de2a))
+* modified training pipeline ([9f9140c](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/9f9140cb585345cd244a1dfee1a06e51a5f7f7a8))
+* **official-bots:** configure JWT verification ([#72](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/72)) ([98c64fc](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/98c64fc0d56dc542beb31c75f4b9056d91de03cd))
+* **official-bots:** correct parkOn path from /api/bots to /api/account/bots ([1be9949](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/1be9949c0b5c6a1db535696620d77735050d6c93))
+* **official-bots:** derive tournament game color from game endpoint ([#79](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/79)) ([bfc4672](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/bfc46723e615bb9b65f7f9bba5f53877c4f079a7))
+* **official-bots:** discover tournament games by polling, not just the stream ([10113fd](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/10113fd0579b614d15870798d933bc9c495d2049))
+* **official-bots:** make botToken optional, fall back to env, fix 502 status ([f43d193](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/f43d1930d80670d810c57b54eaa3789854fa082c))
+* **official-bots:** NCS-70-auto-register official bots with account service ([#59](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/59)) ([7117a93](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/7117a93376272094d0b1a6abf2121254ce396684))
+* **official-bots:** park on external tournament servers using correct endpoint and token ([3188241](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/31882417377468b41bbe3ff94506aa4928024450))
+* **official-bots:** play games by polling state instead of NDJSON stream ([bfb15c7](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/bfb15c7299bd471d5e064a577ed10af98e2ea90a))
+* **official-bots:** play only own tournament games with correct color ([4651bb7](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/4651bb796f07a21bd013d9521b2dfe2e1078cebb))
+* **official-bots:** prevent Colab OOM in NNUE training ([e2b4342](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/e2b4342f602215b5e8de6fccafc4105525a1ddd1))
+* **official-bots:** prioritize Redis token over stale env var in joinTournament ([83dd2d4](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/83dd2d4335ca48eb3e5aa234a75367574276ba63))
+* **official-bots:** register with tournament server directly to get correct token ([64b5d55](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/64b5d5567f110c2fe152558c7de275a1e0b30e21))
+* **official-bots:** resolve per-difficulty bot token on tournament join ([fdf4c94](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/fdf4c94811d086996447bb4657fac1d9bd6e5a93))
+* **official-bots:** resume tournaments already joined after restart ([285b73e](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/285b73efbd6dd98cec410ade9eead9881d693a8f))
+* **official-bots:** stream NNUE features as sparse indices to stop host OOM ([9d65662](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/9d656624d85889f55746faa5704578e248f9b088))
+* **official-bots:** sync bots before token fetch on first startup after DB wipe ([b0ddb27](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/b0ddb274d23bca8b1b3f691ce0d643f33e0b54cd))
+* **official-bots:** use ThreadLocalRandom in PolyglotBook for native image ([1b30c3b](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/1b30c3be393d25712c8743d3d9057207f8bbb67c))
+
+### Reverts
+
+* Revert "refactor: update metrics paths formatting in application.yml for clarity" ([3870566](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/38705663498d5f47c40dafe2f26198589ede8656))
+##  (2026-06-30)
+
+### Features
+
+* add initialization metrics for various services ([d438e97](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/d438e97f32bdde0bfc63c1b4a8cc810cdd093166))
+* add OpenTelemetry trace configuration with parentbased sampler ([3904d5a](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/3904d5ad8ad4930ddee65287a7bfab785a6148f5))
+* **analytics:** add Spark batch analytics module ([#70](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/70)) ([39f1657](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/39f1657e1db6e84889af338c43be8cb5c03c3ec3))
+* **config:** update application.yml for PostgreSQL and remove staging/production configurations ([2404e61](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/2404e6164c3b50ffccbea5238d636060d6abe4d6))
+* **config:** update application.yml for staging and production environments ([6113432](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/6113432a14c476a3a0dfc0d449e17d023697f2ba))
+* configure logging and add OpenTelemetry support ([#49](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/49)) ([d57c488](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/d57c4886612d1d92da0e1b79209fc83e6ef537a1))
+* **docker:** add .dockerignore and .gitignore files for build exclusions ([c987d8e](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/c987d8e258c0e6c4cfbdaa8381c64c410d7a2b83))
+* **docker:** add Dockerfiles for building Quarkus application in native and JVM modes ([3f2d2bb](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/3f2d2bb4c97fa8cddba66e1da4427c54236dfeed))
+* **docker:** add Dockerfiles for Quarkus application in JVM and native modes ([34b9933](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/34b993304670cf2aa62cd2f6460cee7b9864b08e))
+* **events:** migrate game-creation and bot flows to Redis Streams NCS-89 ([#62](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/62)) ([a24924c](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/a24924c23057db3d700a75dbc4333557789cd991))
+* **ncs-110:** feed NNUE root-move scores into search move ordering ([#83](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/83)) ([e4fee85](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/e4fee8513430093d46957970618935e99591519f))
+* NCS-78 Add Traceability to the Applications ([#46](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/46)) ([649566e](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/649566eb3fcf38f91c8896a739f74ea318af312d))
+* NCS-78 Add Traceability to the Applications ([#47](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/47)) ([87dfc6c](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/87dfc6c2bcce7f7d58fc641bd8d468a2e584c108))
+* NCS-82 add Swiss-system tournament module ([#55](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/55)) ([c5661de](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/c5661de4a0ebf4b33211f5a391840dcf744656b7))
+* **official-bots:** activate opening book in expert bot (native-safe) ([260db25](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/260db25803ec55ce99e55782791eabdc190dfed4))
+* **official-bots:** add Google Colab notebook for NNUE training (NCS-111) ([#81](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/81)) ([fa10852](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/fa10852bc98451d4068ec6fb9e7a486b5e53ef5c))
+* **official-bots:** consume GameOver stream for bot cleanup ([#67](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/67)) ([db9d153](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/db9d1533912f4b41c4d1ca80ccffdde5d23d6ff6))
+* **official-bots:** implement king-relative (HalfKP) encoding in NNUE (NCS-109) ([#80](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/80)) ([44f376f](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/44f376f03221f086b898741436e13c93fd314dd1))
+* **official-bots:** make HybridBot veto actionable and use it for expert ([1df29cf](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/1df29cf3a6e21af3f396b2b7a6da67d978f941ae))
+* **official-bots:** park expert bot on tournament server at startup ([#75](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/75)) ([30295a4](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/30295a4bb95855ee8261c92278bb9ebc80ee12ee))
+* **official-bots:** resolve tournament bot token from Redis and account service ([386ddc5](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/386ddc5c19f8f893b16c6422aa5393b54c872e45))
+* **official-bots:** standalone self-play + one-shot dataset builder for NNUE training ([1c80abd](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/1c80abdb8a45814d642d43c633cde81ce7374c4f))
+* **tournament:** auto-join external tournaments and publish created ones ([#77](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/77)) ([9978b7e](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/9978b7ea78eb658a225a461b9cd339386c0c14f3))
+* **tournament:** federate tournaments across clusters with DB replication ([5b000a6](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/5b000a6e5f04ea6770d1c7ab6bfdaded77a99172))
+* **tournament:** seed external server registry from env var on startup ([845dc9c](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/845dc9c2935c8bc1be42541dfaf31c9a861d3272))
+* true-microservices ([#40](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/40)) ([5909242](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/590924254e8a2754de661a57a03e43f89ceb6299))
+
+### Bug Fixes
+
+* **bot:** include quiet promotions in quiescence search ([4938560](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/49385600147021cd29f00a8eecc6be7ba8470717))
+* **bot:** seed search with game history, add contempt and NNUE mop-up ([faf7eb3](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/faf7eb38ea7a0d3bc41ae4c2ef9a5195822f390c))
+* enable official bots to connect to external tournament server ([#71](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/71)) ([688d30e](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/688d30e2b10026923372be5fca3c63eaaee2de2a))
+* modified training pipeline ([9f9140c](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/9f9140cb585345cd244a1dfee1a06e51a5f7f7a8))
+* **official-bots:** configure JWT verification ([#72](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/72)) ([98c64fc](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/98c64fc0d56dc542beb31c75f4b9056d91de03cd))
+* **official-bots:** correct parkOn path from /api/bots to /api/account/bots ([1be9949](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/1be9949c0b5c6a1db535696620d77735050d6c93))
+* **official-bots:** derive tournament game color from game endpoint ([#79](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/79)) ([bfc4672](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/bfc46723e615bb9b65f7f9bba5f53877c4f079a7))
+* **official-bots:** discover tournament games by polling, not just the stream ([10113fd](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/10113fd0579b614d15870798d933bc9c495d2049))
+* **official-bots:** make botToken optional, fall back to env, fix 502 status ([f43d193](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/f43d1930d80670d810c57b54eaa3789854fa082c))
+* **official-bots:** NCS-70-auto-register official bots with account service ([#59](https://git.janis-eccarius.de/NowChess/NowChessSystems/issues/59)) ([7117a93](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/7117a93376272094d0b1a6abf2121254ce396684))
+* **official-bots:** park on external tournament servers using correct endpoint and token ([3188241](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/31882417377468b41bbe3ff94506aa4928024450))
+* **official-bots:** play games by polling state instead of NDJSON stream ([bfb15c7](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/bfb15c7299bd471d5e064a577ed10af98e2ea90a))
+* **official-bots:** play only own tournament games with correct color ([4651bb7](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/4651bb796f07a21bd013d9521b2dfe2e1078cebb))
+* **official-bots:** prevent Colab OOM in NNUE training ([e2b4342](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/e2b4342f602215b5e8de6fccafc4105525a1ddd1))
+* **official-bots:** prioritize Redis token over stale env var in joinTournament ([83dd2d4](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/83dd2d4335ca48eb3e5aa234a75367574276ba63))
+* **official-bots:** register with tournament server directly to get correct token ([64b5d55](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/64b5d5567f110c2fe152558c7de275a1e0b30e21))
+* **official-bots:** resolve per-difficulty bot token on tournament join ([fdf4c94](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/fdf4c94811d086996447bb4657fac1d9bd6e5a93))
+* **official-bots:** resume tournaments already joined after restart ([285b73e](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/285b73efbd6dd98cec410ade9eead9881d693a8f))
+* **official-bots:** stream NNUE features as sparse indices to stop host OOM ([9d65662](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/9d656624d85889f55746faa5704578e248f9b088))
+* **official-bots:** sync bots before token fetch on first startup after DB wipe ([b0ddb27](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/b0ddb274d23bca8b1b3f691ce0d643f33e0b54cd))
+* **official-bots:** use ThreadLocalRandom in PolyglotBook for native image ([1b30c3b](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/1b30c3be393d25712c8743d3d9057207f8bbb67c))
+
+### Reverts
+
+* Revert "refactor: update metrics paths formatting in application.yml for clarity" ([3870566](https://git.janis-eccarius.de/NowChess/NowChessSystems/commit/38705663498d5f47c40dafe2f26198589ede8656))
@@ -92,28 +92,7 @@
   "execution_count": null,
   "metadata": {},
   "outputs": [],
-   "source": [
-    "from train import train_nnue, burst_train, DEFAULT_HIDDEN_SIZES\n",
-    "\n",
-    "WEIGHTS_DIR = Path(DRIVE_ROOT) / 'weights'\n",
-    "WEIGHTS_DIR.mkdir(parents=True, exist_ok=True)\n",
-    "OUTPUT_FILE = str(WEIGHTS_DIR / 'nnue_weights.pt')\n",
-    "\n",
-    "# ── Training hyperparameters ──────────────────────────────────────────────────\n",
-    "HIDDEN_SIZES      = DEFAULT_HIDDEN_SIZES   # [1536, 1024, 512, 256]\n",
-    "BATCH_SIZE        = 16384\n",
-    "EPOCHS            = 100\n",
-    "EARLY_STOPPING    = 10                     # None to disable\n",
-    "SUBSAMPLE_RATIO   = 1.0\n",
-    "\n",
-    "# Resume from latest checkpoint if one exists\n",
-    "checkpoints = sorted(WEIGHTS_DIR.glob('nnue_weights_v*.pt'))\n",
-    "CHECKPOINT = str(checkpoints[-1]) if checkpoints else None\n",
-    "if CHECKPOINT:\n",
-    "    print(f'Resuming from checkpoint: {CHECKPOINT}')\n",
-    "else:\n",
-    "    print('Starting training from scratch.')"
-   ],
+   "source": "from train import train_nnue, burst_train, DEFAULT_HIDDEN_SIZES\n\nWEIGHTS_DIR = Path(DRIVE_ROOT) / 'weights'\nWEIGHTS_DIR.mkdir(parents=True, exist_ok=True)\nOUTPUT_FILE = str(WEIGHTS_DIR / 'nnue_weights.pt')\n\n# ── Training hyperparameters ──────────────────────────────────────────────────\nHIDDEN_SIZES      = DEFAULT_HIDDEN_SIZES\n# Features are streamed as sparse indices and densified on the GPU per batch, so\n# host RAM is no longer the limit — GPU memory is. A dense batch is\n# batch_size * 98304 * 4 bytes on the GPU (~3.2 GB at 8192 on a 16 GB T4).\nBATCH_SIZE        = 8192\nEPOCHS            = 100\nEARLY_STOPPING    = 10                     # None to disable\nSUBSAMPLE_RATIO   = 1.0\n\n# Resume from latest checkpoint if one exists\ncheckpoints = sorted(WEIGHTS_DIR.glob('nnue_weights_v*.pt'))\nCHECKPOINT = str(checkpoints[-1]) if checkpoints else None\nif CHECKPOINT:\n    print(f'Resuming from checkpoint: {CHECKPOINT}')\nelse:\n    print('Starting training from scratch.')",
   "id": "train-config"
  },
  {
@@ -13,6 +13,11 @@ import chess
 from datetime import datetime, timedelta
 import re
 import numpy as np
+import os
+
+# DataLoader workers: cap to the machine's CPUs (Colab free tier = 2). Too many
+# workers each fork the dataset and OOM-kill the runtime.
+LOADER_WORKERS = int(os.environ.get("NNUE_LOADER_WORKERS", min(4, os.cpu_count() or 2)))


 def _shard_files(data_file):
@@ -77,9 +82,12 @@ class NNUEDataset(Dataset):
    def __getitem__(self, idx):
        fen = self.positions[idx]
        eval_val = self.evals[idx]
-        features = fen_to_features(fen)
+        # Return only the active feature indices (~64), not a dense 98304-dim vector.
+        # The training loop scatters these into a dense batch on the GPU, keeping host
+        # RAM tiny. Densifying per-item here OOM-kills the runtime.
+        indices = fen_to_indices(fen)

-        # Board is flipped for Black-to-move in fen_to_features; negate eval
+        # Board is flipped for Black-to-move in fen_to_indices; negate eval
        # so the label still means "good for the side shown as White after flip"
        if ' b ' in fen:
            eval_val = -eval_val
@@ -90,7 +98,7 @@ class NNUEDataset(Dataset):
        else:
            target = torch.sigmoid(torch.tensor(eval_val / 400.0, dtype=torch.float32))

-        return features, target
+        return indices, target

 # King-relative (HalfKP) encoding: two perspectives, one per side's king.
 # Each piece is encoded as:  kingSq * 768 + pieceIdx * 64 + sq
@@ -105,14 +113,14 @@ _PIECE_TO_IDX = {
 }


-def fen_to_features(fen):
-    """Convert FEN to 98304-dim king-relative (HalfKP) feature vector.
+def fen_to_indices(fen):
+    """Active king-relative (HalfKP) feature indices for a FEN (~64 entries).

    For Black-to-move positions the board is mirrored (ranks flipped, colours
    swapped) so the network always sees the position from the side-to-move's
-    perspective.  The caller is responsible for negating the eval label to match.
+    perspective. The caller is responsible for negating the eval label to match.
    """
-    features = torch.zeros(INPUT_SIZE, dtype=torch.float32)
+    indices = []
    try:
        board = chess.Board(fen)
        # Perspective flip: present all positions as if White is to move
@@ -121,20 +129,41 @@ def fen_to_features(fen):
        wk = board.king(chess.WHITE)
        bk = board.king(chess.BLACK)
        if wk is None or bk is None:
-            return features
+            return torch.zeros(0, dtype=torch.long)
        for sq in chess.SQUARES:
            piece = board.piece_at(sq)
            if piece is None:
                continue
            pidx = _PIECE_TO_IDX[piece.symbol()]
            # White-king perspective (indices 0 .. _HALF_SIZE-1)
-            features[wk * 768 + pidx * 64 + sq] = 1.0
+            indices.append(wk * 768 + pidx * 64 + sq)
            # Black-king perspective (indices _HALF_SIZE .. INPUT_SIZE-1)
-            features[_HALF_SIZE + bk * 768 + pidx * 64 + sq] = 1.0
+            indices.append(_HALF_SIZE + bk * 768 + pidx * 64 + sq)
    except Exception:
-        pass
+        return torch.zeros(0, dtype=torch.long)
+    return torch.tensor(indices, dtype=torch.long)
+
+
+def fen_to_features(fen):
+    """Dense 98304-dim HalfKP vector. Kept for external callers; training uses the
+    sparse indices + GPU scatter path instead (see _collate_sparse)."""
+    features = torch.zeros(INPUT_SIZE, dtype=torch.float32)
+    features[fen_to_indices(fen)] = 1.0
    return features

+
+def _collate_sparse(batch):
+    """Collate (indices, target) items into (row_idx, col_idx, batch_size), targets.
+
+    Row/col index pairs address the active features of a dense [B, INPUT_SIZE] tensor
+    that the training loop allocates on the GPU — so the host only ever holds the
+    sparse indices, never a dense batch."""
+    idx_list, targets = zip(*batch)
+    rows = torch.cat([torch.full((idx.numel(),), i, dtype=torch.long)
+                      for i, idx in enumerate(idx_list)])
+    cols = torch.cat(idx_list)
+    return (rows, cols, len(idx_list)), torch.stack(targets)
+
 # Smaller hidden layers are appropriate: the L1 input is very sparse (~64 active
 # features out of 98304) so the L1 itself is cheap to update incrementally; the
 # larger capacity comes from the wider perspective encoding, not deeper layers.
@@ -256,17 +285,19 @@ def _setup_training(data_file, batch_size, subsample_ratio):
        train_dataset,
        batch_size=batch_size,
        sampler=train_sampler,
-        num_workers=8,
+        num_workers=LOADER_WORKERS,
        pin_memory=True,
-        persistent_workers=True
+        persistent_workers=LOADER_WORKERS > 0,
+        collate_fn=_collate_sparse,
    )
    val_loader = DataLoader(
        val_dataset,
        batch_size=batch_size,
        shuffle=False,
-        num_workers=8,
+        num_workers=LOADER_WORKERS,
        pin_memory=True,
-        persistent_workers=True
+        persistent_workers=LOADER_WORKERS > 0,
+        collate_fn=_collate_sparse,
    )

    return device, dataset, train_dataset, val_dataset, train_loader, val_loader, num_positions
@@ -304,8 +335,9 @@ def _run_training_season(
        model.train()
        train_loss = 0.0
        with tqdm(total=len(train_loader), desc=f"Epoch {epoch_display}/{total_epochs} - Train") as pbar:
-            for batch_features, batch_targets in train_loader:
-                batch_features = batch_features.to(device)
+            for (rows, cols, bsz), batch_targets in train_loader:
+                batch_features = torch.zeros(bsz, INPUT_SIZE, device=device)
+                batch_features[rows.to(device), cols.to(device)] = 1.0
                batch_targets = batch_targets.to(device).unsqueeze(1)

                optimizer.zero_grad()
@@ -318,7 +350,7 @@ def _run_training_season(
                scaler.step(optimizer)
                scaler.update()

-                train_loss += loss.item() * batch_features.size(0)
+                train_loss += loss.item() * bsz
                pbar.update(1)

        train_loss /= len(train_dataset)
@@ -328,14 +360,15 @@ def _run_training_season(
        val_loss = 0.0
        with torch.no_grad():
            with tqdm(total=len(val_loader), desc=f"Epoch {epoch_display}/{total_epochs} - Val") as pbar:
-                for batch_features, batch_targets in val_loader:
-                    batch_features = batch_features.to(device)
+                for (rows, cols, bsz), batch_targets in val_loader:
+                    batch_features = torch.zeros(bsz, INPUT_SIZE, device=device)
+                    batch_features[rows.to(device), cols.to(device)] = 1.0
                    batch_targets = batch_targets.to(device).unsqueeze(1)

                    with torch.amp.autocast('cuda' if torch.cuda.is_available() else 'cpu'):
                        outputs = model(batch_features)
                        loss = criterion(outputs, batch_targets)
-                    val_loss += loss.item() * batch_features.size(0)
+                    val_loss += loss.item() * bsz
                    pbar.update(1)

        val_loss /= len(val_dataset)
@@ -12,7 +12,7 @@ object EvaluationNNUE extends Evaluation:
  val DRAW_SCORE: Int      = 0

  /** Full-board evaluate — used as fallback and by non-search callers. */
-  def evaluate(context: GameContext): Int = nnue.evaluate(context)
+  def evaluate(context: GameContext): Int = nnue.evaluate(context) + MopUp.score(context)

  // ── Accumulator hooks (incremental L1) ───────────────────────────────────

@@ -28,4 +28,4 @@ object EvaluationNNUE extends Evaluation:
    else nnue.pushAccumulator(childPly, move, parent.board, child.board)

  override def evaluateAccumulator(ply: Int, context: GameContext, hash: Long): Int =
-    nnue.evaluateAtPlyWithValidation(ply, context.turn, hash, context.board)
+    nnue.evaluateAtPlyWithValidation(ply, context.turn, hash, context.board) + MopUp.score(context)
@@ -0,0 +1,60 @@
+package de.nowchess.bot.bots.nnue
+
+import de.nowchess.api.board.{Color, PieceType, Square}
+import de.nowchess.api.game.GameContext
+
+/** Endgame "mop-up" correction for the NNUE evaluation.
+  *
+  * Pure NNUE lacks explicit mating knowledge, so KX-vs-K conversions stall. When one side is reduced to a lone king and
+  * the other holds sufficient mating material, this term rewards driving the bare king to the edge and walking the
+  * winning king in. Returns a value from the side-to-move perspective (positive = good for side to move). Zero in any
+  * position that is not a lone-king endgame, so middlegame NNUE output is untouched.
+  */
+object MopUp:
+
+  private val EDGE_WEIGHT      = 10
+  private val PROXIMITY_WEIGHT = 4
+  private val MIN_WINNER_VALUE = 400
+
+  def score(context: GameContext): Int =
+    loneKingColor(context) match
+      case None => 0
+      case Some(loser) =>
+        val winner = loser.opposite
+        if winnerValue(context, winner) < MIN_WINNER_VALUE then 0
+        else mopUp(context, winner, loser) * (if context.turn == winner then 1 else -1)
+
+  private def mopUp(context: GameContext, winner: Color, loser: Color): Int =
+    (for
+      loserKing  <- context.kingSquare(loser)
+      winnerKing <- context.kingSquare(winner)
+    yield EDGE_WEIGHT * centerDistance(loserKing) +
+      PROXIMITY_WEIGHT * (14 - kingDistance(winnerKing, loserKing))).getOrElse(0)
+
+  private def loneKingColor(context: GameContext): Option[Color] =
+    val nonKing = context.board.pieces.values.filter(_.pieceType != PieceType.King)
+    val whiteHasOther = nonKing.exists(_.color == Color.White)
+    val blackHasOther = nonKing.exists(_.color == Color.Black)
+    if whiteHasOther == blackHasOther then None
+    else if whiteHasOther then Some(Color.Black)
+    else Some(Color.White)
+
+  private def winnerValue(context: GameContext, winner: Color): Int =
+    context.board.pieces.values.foldLeft(0) { (sum, piece) =>
+      if piece.color != winner then sum
+      else
+        sum + (piece.pieceType match
+          case PieceType.Queen  => 900
+          case PieceType.Rook   => 500
+          case PieceType.Bishop => 330
+          case PieceType.Knight => 320
+          case _                => 0)
+    }
+
+  private def centerDistance(sq: Square): Int =
+    val fileDist = math.max(3 - sq.file.ordinal, sq.file.ordinal - 4)
+    val rankDist = math.max(3 - sq.rank.ordinal, sq.rank.ordinal - 4)
+    fileDist + rankDist
+
+  private def kingDistance(a: Square, b: Square): Int =
+    (a.file.ordinal - b.file.ordinal).abs + (a.rank.ordinal - b.rank.ordinal).abs
@@ -1,6 +1,6 @@
 package de.nowchess.bot.logic

-import de.nowchess.api.board.PieceType
+import de.nowchess.api.board.{CastlingRights, PieceType}
 import de.nowchess.api.game.GameContext
 import de.nowchess.api.move.{Move, MoveType}
 import de.nowchess.bot.ai.Evaluation
@@ -26,6 +26,7 @@ final class AlphaBetaSearch(
  private val TIME_CHECK_FREQUENCY = 1000
  private val FUTILITY_MARGIN      = 100
  private val CHECK_EXTENSION      = 1
+  private val CONTEMPT             = 25

  private val timeStartMs = AtomicLong(0L)
  private val timeLimitMs = AtomicLong(0L)
@@ -67,6 +68,7 @@ final class AlphaBetaSearch(
    timeLimitMs.set(Long.MaxValue / 4)
    nodeCount.set(0)
    val rootHash = ZobristHash.hash(context)
+    val history  = historyCounts(context)
    (1 to maxDepth)
      .foldLeft((None: Option[Move], 0)) { case ((bestSoFar, prevScore), depth) =>
        val (alpha, beta) =
@@ -78,6 +80,7 @@ final class AlphaBetaSearch(
          beta,
          ASPIRATION_DELTA,
          rootHash,
+          history,
          excludedRootMoves,
          hints,
        )
@@ -115,6 +118,7 @@ final class AlphaBetaSearch(
    timeLimitMs.set(timeBudgetMs)
    nodeCount.set(0)
    val rootHash = ZobristHash.hash(context)
+    val history  = historyCounts(context)

    @scala.annotation.tailrec
    def loop(bestSoFar: Option[Move], prevScore: Int, depth: Int, lastDepth: Int): (Option[Move], Int) =
@@ -129,6 +133,7 @@ final class AlphaBetaSearch(
          beta,
          ASPIRATION_DELTA,
          rootHash,
+          history,
          excludedRootMoves,
          hints,
        )
@@ -154,10 +159,11 @@ final class AlphaBetaSearch(
      beta: Int,
      initialWindow: Int,
      rootHash: Long,
+      history: Map[Long, Int],
      excludedRootMoves: Set[Move],
      hints: Map[Move, Int],
  ): (Int, Option[Move]) =
-    val state = SearchState(rootHash, Map(rootHash -> 1))
+    val state = SearchState(rootHash, history)

    @scala.annotation.tailrec
    def loop(currentAlpha: Int, currentBeta: Int, delta: Int, attempt: Int): (Int, Option[Move]) =
@@ -173,6 +179,32 @@ final class AlphaBetaSearch(

    loop(alpha, beta, initialWindow, 0)

+  private def drawScore(ply: Int): Int =
+    if ply % 2 == 0 then weights.DRAW_SCORE - CONTEMPT else weights.DRAW_SCORE + CONTEMPT
+
+  private def historyCounts(context: GameContext): Map[Long, Int] =
+    val initialTurn = if context.moves.size % 2 == 0 then context.turn else context.turn.opposite
+    val root = GameContext(
+      board = context.initialBoard,
+      turn = initialTurn,
+      castlingRights = CastlingRights.Initial,
+      enPassantSquare = None,
+      halfMoveClock = 0,
+      moves = List.empty,
+    )
+    val rootHash = ZobristHash.hash(root)
+    context.moves
+      .foldLeft((root, rootHash, List(rootHash))) { case ((cur, curHash, acc), move) =>
+        val next     = rules.applyMove(cur)(move)
+        val nextHash = ZobristHash.nextHash(cur, curHash, move, next)
+        (next, nextHash, nextHash :: acc)
+      }
+      ._3
+      .groupBy(identity)
+      .view
+      .mapValues(_.size)
+      .toMap
+
  private def hasNonPawnMaterial(context: GameContext): Boolean =
    context.board.pieces.values.exists { piece =>
      piece.color == context.turn &&
@@ -226,7 +258,8 @@ final class AlphaBetaSearch(
  ): Option[(Int, Option[Move])] =
    if count % TIME_CHECK_FREQUENCY == 0 && isOutOfTime then
      Some((weights.evaluateAccumulator(params.ply, params.context, params.state.hash), None))
-    else if params.state.repetitions.getOrElse(params.state.hash, 0) >= 3 then Some((weights.DRAW_SCORE, None))
+    else if params.ply > 0 && params.state.repetitions.getOrElse(params.state.hash, 0) >= 2 then
+      Some((drawScore(params.ply), None))
    else ttCutoff(params)

  private def ttCutoff(params: SearchParams): Option[(Int, Option[Move])] =
@@ -248,12 +281,12 @@ final class AlphaBetaSearch(
    if legalMoves.isEmpty then
      Some(
        (
-          if rules.isCheckmate(params.context) then -(weights.CHECKMATE_SCORE - params.ply) else weights.DRAW_SCORE,
+          if rules.isCheckmate(params.context) then -(weights.CHECKMATE_SCORE - params.ply) else drawScore(params.ply),
          None,
        ),
      )
    else if rules.isInsufficientMaterial(params.context) || rules.isFiftyMoveRule(params.context) then
-      Some((weights.DRAW_SCORE, None))
+      Some((drawScore(params.ply), None))
    else if params.depth == 0 then
      Some((quiescence(params.context, params.ply, params.window.alpha, params.window.beta, params.state.hash), None))
    else None
@@ -468,5 +501,5 @@ final class AlphaBetaSearch(
  private def isCapture(context: GameContext, move: Move): Boolean = move.moveType match
    case MoveType.Normal(true) => true
    case MoveType.EnPassant    => true
-    case MoveType.Promotion(_) => context.board.pieceAt(move.to).exists(_.color != context.turn)
+    case MoveType.Promotion(_) => true
    case _                     => false
@@ -253,6 +253,30 @@ class AlphaBetaSearchTest extends AnyFunSuite with Matchers:
    val search = AlphaBetaSearch(promoCaptureRules, weights = EvaluationClassic)
    search.bestMove(ctx, maxDepth = 1) should be(Some(promoCapture))

+  test("quiet promotion is treated as tactical in quiescence"):
+    // Pawn pushes to an empty back-rank square (no capture). Must still be searched in
+    // quiescence so a bot does not skip queening at the search horizon.
+    val quietPromo = Move(Square(File.E, Rank.R7), Square(File.E, Rank.R8), MoveType.Promotion(PromotionPiece.Queen))
+    val board = Board(
+      Map(
+        Square(File.E, Rank.R7) -> Piece.WhitePawn,
+      ),
+    )
+    val ctx = GameContext.initial.withBoard(board).withTurn(Color.White)
+    val quietPromoRules = new RuleSet:
+      def candidateMoves(context: GameContext)(square: Square): List[Move] = Nil
+      def legalMoves(context: GameContext)(square: Square): List[Move]     = Nil
+      def allLegalMoves(context: GameContext): List[Move]                  = List(quietPromo)
+      def isCheck(context: GameContext): Boolean                           = false
+      def isCheckmate(context: GameContext): Boolean                       = false
+      def isStalemate(context: GameContext): Boolean                       = false
+      def isInsufficientMaterial(context: GameContext): Boolean            = false
+      def isFiftyMoveRule(context: GameContext): Boolean                   = false
+      def isThreefoldRepetition(context: GameContext): Boolean             = false
+      def applyMove(context: GameContext)(move: Move): GameContext         = context
+    val search = AlphaBetaSearch(quietPromoRules, weights = EvaluationClassic)
+    search.bestMove(ctx, maxDepth = 1) should be(Some(quietPromo))
+
  test("draw when isInsufficientMaterial with legal moves present"):
    val legalMove = Move(Square(File.E, Rank.R2), Square(File.E, Rank.R4), MoveType.Normal())
    val drawRules = new RuleSet:
@@ -0,0 +1,34 @@
+package de.nowchess.bot
+
+import de.nowchess.api.board.{Board, Color, File, Piece, Rank, Square}
+import de.nowchess.api.game.GameContext
+import de.nowchess.bot.bots.nnue.MopUp
+import org.scalatest.funsuite.AnyFunSuite
+import org.scalatest.matchers.should.Matchers
+
+class MopUpTest extends AnyFunSuite with Matchers:
+
+  private def ctx(turn: Color, pieces: (Square, Piece)*): GameContext =
+    GameContext.initial.withBoard(Board(pieces.toMap)).withTurn(turn)
+
+  private val wk = Square(File.E, Rank.R1) -> Piece.WhiteKing
+  private val wq = Square(File.D, Rank.R1) -> Piece.WhiteQueen
+  private val bkCorner = Square(File.H, Rank.R8) -> Piece.BlackKing
+  private val bkCenter = Square(File.D, Rank.R4) -> Piece.BlackKing
+
+  test("zero in a balanced middlegame-like position (both sides have material)"):
+    MopUp.score(ctx(Color.White, wk, wq, bkCorner, Square(File.A, Rank.R8) -> Piece.BlackQueen)) should be(0)
+
+  test("zero when winner lacks mating material (lone king vs king)"):
+    MopUp.score(ctx(Color.White, wk, bkCorner)) should be(0)
+
+  test("positive for the winning side to move in KQ vs K"):
+    MopUp.score(ctx(Color.White, wk, wq, bkCorner)) should be > 0
+
+  test("negative for the bare-king side to move in KQ vs K"):
+    MopUp.score(ctx(Color.Black, wk, wq, bkCorner)) should be < 0
+
+  test("cornered bare king scores higher than centralized bare king"):
+    val cornered    = MopUp.score(ctx(Color.White, wk, wq, bkCorner))
+    val centralized = MopUp.score(ctx(Color.White, wk, wq, bkCenter))
+    cornered should be > centralized
@@ -1,3 +1,3 @@
 MAJOR=0
-MINOR=39
+MINOR=42
 PATCH=0
Author	SHA1	Message	Date
TeamCity	7136803c7e	ci: bump version with Build-160	2026-06-30 10:21:06 +00:00
Janis	faf7eb38ea	fix(bot): seed search with game history, add contempt and NNUE mop-up Build & Test (NowChessSystems) TeamCity build finished Details Repetition: alpha-beta seeded the repetition map with only the root position, so search was blind to positions already reached in the real game and would happily shuffle into draws when ahead. Reconstruct the full game-history position hashes by replaying moves and seed the search state with them; treat a twofold occurrence at non-root nodes as a draw. Contempt: draws are now scored CONTEMPT (25cp) away from zero, signed by ply parity, so the bot avoids dead-equal repetitions instead of settling. Endgame: pure NNUE lacks mating knowledge and stalls KX-vs-K conversions. Add a MopUp correction (edge-driving + king-proximity) applied only in lone-king endgames with sufficient mating material; zero elsewhere so middlegame NNUE output is untouched. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>	2026-06-30 12:04:27 +02:00
TeamCity	344bed6935	ci: bump version with Build-159	2026-06-29 17:34:14 +00:00
Janis Eccarius	4938560014	fix(bot): include quiet promotions in quiescence search Build & Test (NowChessSystems) TeamCity build finished Details Quiescence tactical filter only flagged capture-promotions, so a quiet queening on an empty back-rank square was treated as non-tactical and skipped at the search horizon. A bot could therefore miss a winning promotion sitting exactly at the horizon and play another move. All bots (Classical/NNUE/Hybrid) share AlphaBetaSearch and were affected. Treat every promotion as tactical so quiescence always expands it. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>	2026-06-29 19:18:31 +02:00
TeamCity	4a397eed7f	ci: bump version with Build-158	2026-06-24 20:41:25 +00:00
Janis Eccarius	9d656624d8	fix(official-bots): stream NNUE features as sparse indices to stop host OOM Build & Test (NowChessSystems) TeamCity build finished Details Densifying the 98304-dim HalfKP vector per item filled host RAM and crashed the Colab runtime even at small batch sizes. The dataset now yields only the ~64 active feature indices; a custom collate carries (row, col) pairs and the training loop scatters them into a dense [B, INPUT_SIZE] tensor on the GPU. Host RAM stays tiny; GPU holds one dense batch transiently. - NNUEDataset.__getitem__ returns indices via new fen_to_indices. - fen_to_features now derives from fen_to_indices (kept for external callers). - _collate_sparse builds row/col index batches; loaders use it. - train/val loops scatter to a GPU dense batch; loss weighting uses batch size. - Notebook: BATCH_SIZE 4096 -> 8192 (host no longer the limit; GPU is). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>	2026-06-24 22:28:53 +02:00
Janis Eccarius	e2b4342f60	fix(official-bots): prevent Colab OOM in NNUE training Build & Test (NowChessSystems) TeamCity build finished Details Dense 98304-dim HalfKP features at batch_size=16384 cost ~6.4 GB/batch on the host; with 8 hardcoded DataLoader workers and prefetch this OOM-killed the Colab runtime. - train.py: adaptive DataLoader workers (min(4, cpu_count), Colab free tier = 2), overridable via NNUE_LOADER_WORKERS; persistent_workers only when > 0. - NNUETraining.ipynb: lower BATCH_SIZE 16384 -> 4096 with a memory-cost note. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>	2026-06-24 22:18:18 +02:00