Seminar Details
2026-06-04 (13:00) : Human-like game playing beyond behavioral alignment
At Shannon (Maxwell - a.105)
Duration: 60 minutes
Organized by Computer Science and Engineering
Speaker :
Aloïs Rautureau (ENS Rennes)
Abstract :
Game playing systems have been extensively studied with the prospect of improving their playing strength, but little work has been done on making them play "like humans". Such "human-like" systems would have a number of advantages and potential use cases: designers wanting to test early prototypes of their game quickly and extensively, players hoping to learn actionable and realistic strategies, or researchers in humanities trying to better understand how human players approach ancient games. While current approaches center their definition around the Turing test (an agent is human-like if it is indistinguishable from one), and are thus mainly based around imitation learning, we argue that human-like play is broader than move selection. The way humans approach games is deeply rooted in cognition, psychology, and the social context in which they play. This seminar will present exploratory work on defining what "human-like" even means in the context of game playing agents, present methods and algorithms aiming to bridge the gap between human cognition and computational approaches, and discuss future work and research directions that stem from this exploration.