Real World Games Look Like Spinning Tops
Wojciech M. Czarnecki, Gauthier Gidel, Brendan D. Tracey, Karl Tuyls, Shayegan Omidshafiei, David Balduzzi, Max Jaderberg
Abstract
This paper investigates the geometrical properties of real world games (e.g. Tic-Tac-Toe, Go, StarCraft II). We hypothesise that their geometrical structure resembles a spinning top, with the upright axis representing transitive strength, and the radial axis representing the non-transitive dimension, which corresponds to the number of cycles that exist at a particular transitive strength. We prove the existence of this geometry for a wide class of real world games by exposing their temporal nature. Additionally, we show that this unique structure also has consequences for learning -it clarifies why populations of strategies are necessary for training of agents, and how population size relates to the structure of the game. Finally, we empirically validate these claims by using a selection of nine real world two-player zero-sum symmetric games, showing 1) the spinning top structure is revealed and can be easily reconstructed by using a new method of Nash clustering to measure the interaction between transitive and cyclical strategy behaviour, and 2) the effect that population size has on the convergence of learning in these games.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 8bc921d6-ea9c-4c2e-9599-01a3ddef9e64Cited by top-tier papers22
- Language Agents with Reinforcement Learning for Strategic Play in the Werewolf GameZelai Xu, Chao Yu, Fei Fang, Yu Wang et al.ICML 2024 · 145 citations
- Towards Unifying Behavioral and Response Diversity for Open-ended Learning in Zero-sum GamesXiangyu Liu, Hangtian Jia, Ying Wen, Yujing Hu et al.NeurIPS 2021 · 67 citations
- Adversarial Policies Beat Superhuman Go AIsTony Tong Wang, Adam Gleave, Tom Tseng, Kellin Pelrine et al.ICML 2023 · 34 citations
- Policy Space Diversity for Non-Transitive GamesJian Yao, Weiming Liu, Haobo Fu, Yaodong Yang et al.NeurIPS 2023 · 28 citations
- NeuPL: Neural Population LearningSiqi Liu, Luke Marris, Daniel Hennes, Josh Merel et al.ICLR 2022 · 19 citations
Related papers
- Convergence of No-Swap-Regret Dynamics in Self-PlayRenato Paes Leme, Georgios Piliouras, Jon SchneiderNeurIPS 2024 · 3 citations
- Synchronization in Learning in Periodic Zero-Sum Games Triggers Divergence from Nash EquilibriumYuma Fujimoto, Kaito Ariu, Kenshi AbeAAAI 2025 · 4 citations
- Evolutionary Game Theory Squared: Evolving Agents in Endogenously Evolving Zero-Sum GamesStratis Skoulakis, Tanner Fiez, Ryann Sim, Georgios Piliouras et al.AAAI 2021 · 17 citations
- Implicit Learning Dynamics in Stackelberg Games: Equilibria Characterization, Convergence Analysis, and Empirical StudyTanner Fiez, Benjamin Chasnov, Lillian J. RatliffICML 2020 · 144 citations
- Follow-the-Regularized-Leader Routes to Chaos in Routing GamesJakub Bielawski, Thiparat Chotibut, Fryderyk Falniowski, Grzegorz Kosiorowski et al.ICML 2021 · 29 citations
