{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/board-games/papers/2","list_of":"/task/board-games","task":"Board Games","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":2,"pages_in_order":2,"rows_per_page":100,"rows":[101,131],"of":131,"counts":{"archive_papers_tagged":131,"with_a_code_link":60,"where_syntology_ran_a_sample":12,"not_listed_spam_title":0,"listed":131,"listed_where_code_ran":12,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":11,"every_run_a_failure_of_syntologys_instrument":1,"listed_with_a_run_with_no_instrument_failure":11,"listed_every_run_a_failure_of_syntologys_instrument":1,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/board-games","prev":"/task/board-games","next":null,"papers":[{"url":null,"slug":"transfer-of-fully-convolutional-policy-value","title":"Transfer of Fully Convolutional Policy-Value Networks Between Games and Game Variants","date":"2021-02-24","arxiv_id":"2102.12375","repositories_listed":0,"syntology":null},{"url":null,"slug":"solving-qsat-problems-with-neural-mcts","title":"Solving QSAT problems with neural MCTS","date":"2021-01-17","arxiv_id":"2101.06619","repositories_listed":0,"syntology":null},{"url":null,"slug":"strategic-features-for-general-games","title":"Strategic Features for General Games","date":"2021-01-04","arxiv_id":"2101.00843","repositories_listed":0,"syntology":null},{"url":null,"slug":"fever-basketball-a-complex-flexible-and","title":"Fever Basketball: A Complex, Flexible, and Asynchronized Sports Game Environment for Multi-agent Reinforcement Learning","date":"2020-12-06","arxiv_id":"2012.03204","repositories_listed":0,"syntology":null},{"url":null,"slug":"11-teraflops-per-second-photonic","title":"11 TeraFLOPs per second photonic convolutional accelerator for deep learning optical neural networks","date":"2020-11-14","arxiv_id":"2011.07393","repositories_listed":0,"syntology":null},{"url":null,"slug":"playing-carcassonne-with-monte-carlo-tree","title":"Playing Carcassonne with Monte Carlo Tree Search","date":"2020-09-27","arxiv_id":"2009.12974","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-algorithm-for-automatically-updating-a","title":"An Algorithm for Automatically Updating a Forsyth-Edwards Notation String Without an Array Board Representation","date":"2020-09-02","arxiv_id":"2009.03193","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-go-transformer-natural-language-modeling","title":"The Go Transformer: Natural Language Modeling for Game Play","date":"2020-07-07","arxiv_id":"2007.03500","repositories_listed":0,"syntology":null},{"url":null,"slug":"dialogue-policies-for-learning-board-games","title":"Dialogue Policies for Learning Board Games through Multimodal Communication","date":"2020-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"warm-start-alphazero-self-play-search","title":"Warm-Start AlphaZero Self-Play Search Enhancements","date":"2020-04-26","arxiv_id":"2004.12357","repositories_listed":0,"syntology":null},{"url":null,"slug":"polygames-improved-zero-learning","title":"Polygames: Improved Zero Learning","date":"2020-01-27","arxiv_id":"2001.09832","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-mcts-search-with-theoretical-guarantee","title":"A⋆MCTS: SEARCH WITH THEORETICAL GUARANTEE USING POLICY AND VALUE FUNCTIONS","date":"2019-09-25","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"the-many-ai-challenges-of-hearthstone","title":"The Many AI Challenges of Hearthstone","date":"2019-07-15","arxiv_id":"1907.06562","repositories_listed":0,"syntology":null},{"url":null,"slug":"general-board-game-playing-for-education-and","title":"General Board Game Playing for Education and Research in Generic AI Game Learning","date":"2019-07-11","arxiv_id":"1907.06508","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-policies-from-self-play-with-policy","title":"Learning Policies from Self-Play with Policy Gradients and MCTS Value Estimates","date":"2019-05-14","arxiv_id":"1905.05809","repositories_listed":0,"syntology":null},{"url":null,"slug":"creating-pro-level-ai-for-real-time-fighting","title":"Creating Pro-Level AI for a Real-Time Fighting Game Using Deep Reinforcement Learning","date":"2019-04-08","arxiv_id":"1904.03821","repositories_listed":0,"syntology":null},{"url":null,"slug":"improved-reinforcement-learning-with","title":"Improved Reinforcement Learning with Curriculum","date":"2019-03-29","arxiv_id":"1903.12328","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-self-game-play-agents-for","title":"Learning Self-Game-Play Agents for Combinatorial Optimization Problems","date":"2019-03-08","arxiv_id":"1903.03674","repositories_listed":0,"syntology":null},{"url":null,"slug":"at-human-speed-deep-reinforcement-learning","title":"At Human Speed: Deep Reinforcement Learning with Action Delay","date":"2018-10-16","arxiv_id":"1810.07286","repositories_listed":0,"syntology":null},{"url":null,"slug":"transferring-deep-reinforcement-learning-with","title":"Transferring Deep Reinforcement Learning with Adversarial Objective and Augmentation","date":"2018-09-04","arxiv_id":"1809.00770","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-to-shoot-in-first-person-shooter","title":"Learning to Shoot in First Person Shooter Games by Stabilizing Actions and Clustering Rewards for Reinforcement Learning","date":"2018-06-13","arxiv_id":"1806.05117","repositories_listed":0,"syntology":null},{"url":null,"slug":"accounting-for-the-neglected-dimensions-of-ai","title":"Between Progress and Potential Impact of AI: the Neglected Dimensions","date":"2018-06-02","arxiv_id":"1806.00610","repositories_listed":0,"syntology":null},{"url":null,"slug":"embodied-artificial-intelligence-through","title":"Embodied Artificial Intelligence through Distributed Adaptive Control: An Integrated Framework","date":"2017-04-05","arxiv_id":"1704.01407","repositories_listed":0,"syntology":null},{"url":null,"slug":"machine-learning-with-guarantees-using","title":"Machine Learning with Guarantees using Descriptive Complexity and SMT Solvers","date":"2016-09-09","arxiv_id":"1609.02664","repositories_listed":0,"syntology":null},{"url":null,"slug":"simplified-boardgames","title":"Simplified Boardgames","date":"2016-06-08","arxiv_id":"1606.02645","repositories_listed":0,"syntology":null},{"url":null,"slug":"why-artificial-intelligence-needs-a-task","title":"Why Artificial Intelligence Needs a Task Theory --- And What It Might Look Like","date":"2016-04-15","arxiv_id":"1604.04660","repositories_listed":0,"syntology":null},{"url":null,"slug":"building-machines-that-learn-and-think-like","title":"Building Machines That Learn and Think Like People","date":"2016-04-01","arxiv_id":"1604.00289","repositories_listed":0,"syntology":null},{"url":null,"slug":"is-swarm-intelligence-able-to-create-mazes","title":"Is swarm intelligence able to create mazes?","date":"2016-01-25","arxiv_id":"1601.06580","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-generation-of-alternative-starting","title":"Automatic Generation of Alternative Starting Positions for Simple Traditional Board Games","date":"2014-11-14","arxiv_id":"1411.4023","repositories_listed":0,"syntology":null},{"url":null,"slug":"systematic-n-tuple-networks-for-position","title":"Systematic N-tuple Networks for Position Evaluation: Exceeding 90% in the Othello League","date":"2014-06-05","arxiv_id":"1406.1509","repositories_listed":0,"syntology":null},{"url":null,"slug":"evolutionary-search-in-the-space-of-rules-for","title":"Evolutionary Search in the Space of Rules for Creation of New Two-Player Board Games","date":"2014-06-01","arxiv_id":"1406.0175","repositories_listed":0,"syntology":null}],"record_sha256":"1ca770bff2cf295fcd12172700731c477a6641e644befad33ab38b48579b1070","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}