Functional Dynamics by Intention Recognition in Iterated Games
Yuma Fujimoto, Kunihiko Kaneko

TL;DR
This paper introduces a novel game theory framework where players dynamically recognize and adapt to each other's intentions, leading to new equilibrium concepts and insights into strategic interactions.
Contribution
It extends classical game theory by modeling mutual intention recognition as functional dynamics, revealing new equilibria and strategic behaviors.
Findings
Recognition can lead to better payoffs for both players.
New equilibria depend on the degree of mutual recognition.
Recognition influences cooperation and exploitation in games.
Abstract
Intention recognition is an important characteristic of intelligent agents. In their interactions with others, they try to read others' intentions and make an image of others to choose their actions accordingly. While the way in which players choose their actions depending on such intentions has been investigated in game theory, how dynamic changes in intentions by mutually reading others' intentions are incorporated into game theory has not been explored. We present a novel formulation of game theory in which players read others' intentions and change their own through an iterated game. Here, intention is given as a function of the other's action and the own action to be taken accordingly as the dependent variable, while the mutual recognition of intention is represented as the functional dynamics. It is shown that a player suffers no disadvantage when he/she recognizes the other's…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
