Algorithmic Rationality: Game Theory with Costly Computation
Not on the map. Why?
Abstract (arXiv)
We develop a general game-theoretic framework for reasoning about strategic agents performing possibly costly computation. In this framework, many traditional game-theoretic results (such as the existence of a Nash equilibrium) no longer hold. Nevertheless, we can use the framework to provide psychologically appealing explanations of observed behavior in well-studied games (such as finitely repeated prisoner's dilemma and rock-paper-scissors). Furthermore, we provide natural conditions on games sufficient to guarantee that equilibria exist.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Dec 2014.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2024: 1; 2025: 2; 2026: 1.
4 papers.
- 2025Open Challenges in Multi-Agent Security: Towards Secure Systems of Interacting AI Agentscited by 66
- 2024Beyond Preferences in AI Alignmentcited by 46
- 2025Will AI Trade? A Computational Inversion of the No-Trade Theoremcited by 0
- 2026The Value of a Prompt: An LLM-Relative Kolmogorov-Complexity Approachcited by 0
- 2026The Value of a Prompt: An LLM-Relative Kolmogorov-Complexity Approach17 Aug 2026
- 2025Will AI Trade? A Computational Inversion of the No-Trade Theorem17 Dec 2025
- 2025Open Challenges in Multi-Agent Security: Towards Secure Systems of Interacting AI Agents4 May 2025
- 2024Beyond Preferences in AI Alignment30 Aug 2024