Compositional game theory
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Abstract (arXiv)
We introduce open games as a compositional foundation of economic game theory. A compositional approach potentially allows methods of game theory and theoretical computer science to be applied to large-scale economic models for which standard economic tools are not practical. An open game represents a game played relative to an arbitrary environment and to this end we introduce the concept of coutility, which is the utility generated by an open game and returned to its environment. Open games are the morphisms of a symmetric monoidal category and can therefore be composed by categorical composition into sequential move games and by monoidal products into simultaneous move games. Open games can be represented by string diagrams which provide an intuitive but formal visualisation of the information flows. We show that a variety of games can be faithfully represented as open games in the sense of having the same Nash equilibria and off-equilibrium best responses.
Key facts. Cited by 13 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Mar 2016.
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Citing papers per year: 2021: 4; 2022: 1; 2023: 2; 2024: 2; 2025: 3; 2026: 1.
13 papers.
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- 2021Categorical Foundations of Gradient-Based Learningcited by 44
- 2021Compositionality as we see it, everywhere around uscited by 11
- 2021Learners' Languagescited by 6
- 2021How to make qubits speakcited by 5
- 2024Reinforcement Learning in Categorical Cyberneticscited by 4
- 2023The Compositional Structure of Bayesian Inferencecited by 3
- 2023Active Inference in String Diagrams: A Categorical Account of Predictive Processing and Free Energycited by 3
- 2024Deep Learning with Parametric Lensescited by 3
- 2022Space-time tradeoffs of lenses and optics via higher category theorycited by 2
- 2025Cross-Entropy Games for Language Models: From Implicit Knowledge to General Capability Measurescited by 2
- 2026Cognitive Training for Language Models: Towards General Capabilities via Cross-Entropy Gamescited by 2
- 2025AutoBayes: A Compositional Framework for Generalized Variational Inferencecited by 0
1 more
- 2026Cognitive Training for Language Models: Towards General Capabilities via Cross-Entropy Games23 Mar 2026
- 2025Game-Theoretic Gradient Control for Robust Neural Network Training25 Jul 2025
- 2025Cross-Entropy Games for Language Models: From Implicit Knowledge to General Capability Measures7 Jun 2025
- 2025AutoBayes: A Compositional Framework for Generalized Variational Inference24 Mar 2025
- 2024Reinforcement Learning in Categorical Cybernetics3 Apr 2024
- 2024Deep Learning with Parametric Lenses30 Mar 2024
- 2023Active Inference in String Diagrams: A Categorical Account of Predictive Processing and Free Energy1 Aug 2023
- 2023The Compositional Structure of Bayesian Inference10 May 2023
- 2022Space-time tradeoffs of lenses and optics via higher category theory19 Sep 2022
- 2021Compositionality as we see it, everywhere around us11 Oct 2021
- 2021How to make qubits speak2 Jul 2021
- 2021Categorical Foundations of Gradient-Based Learning2 Mar 2021
1 more
- 2021Learners' Languages1 Mar 2021
- 2021Categorical Foundations of Gradient-Based Learningcited by 44
- 2021Compositionality as we see it, everywhere around uscited by 11
- 2021Learners' Languagescited by 6
- 2021How to make qubits speakcited by 5
- 2024Reinforcement Learning in Categorical Cyberneticscited by 4
- 2023The Compositional Structure of Bayesian Inferencecited by 3
- 2023Active Inference in String Diagrams: A Categorical Account of Predictive Processing and Free Energycited by 3
- 2024Deep Learning with Parametric Lensescited by 3
- 2022Space-time tradeoffs of lenses and optics via higher category theorycited by 2
- 2025Cross-Entropy Games for Language Models: From Implicit Knowledge to General Capability Measurescited by 2
- 2026Cognitive Training for Language Models: Towards General Capabilities via Cross-Entropy Gamescited by 2
- 2025AutoBayes: A Compositional Framework for Generalized Variational Inferencecited by 0
12 most cited of 13 All 13 (JSON)
- 2026Cognitive Training for Language Models: Towards General Capabilities via Cross-Entropy Games23 Mar 2026
- 2025Game-Theoretic Gradient Control for Robust Neural Network Training25 Jul 2025
- 2025Cross-Entropy Games for Language Models: From Implicit Knowledge to General Capability Measures7 Jun 2025
- 2025AutoBayes: A Compositional Framework for Generalized Variational Inference24 Mar 2025
- 2024Reinforcement Learning in Categorical Cybernetics3 Apr 2024
- 2024Deep Learning with Parametric Lenses30 Mar 2024
- 2023Active Inference in String Diagrams: A Categorical Account of Predictive Processing and Free Energy1 Aug 2023
- 2023The Compositional Structure of Bayesian Inference10 May 2023
- 2022Space-time tradeoffs of lenses and optics via higher category theory19 Sep 2022
- 2021Compositionality as we see it, everywhere around us11 Oct 2021
- 2021How to make qubits speak2 Jul 2021
- 2021Categorical Foundations of Gradient-Based Learning2 Mar 2021
12 newest of 13 All 13 (JSON)