Game-Theoretic Solvers with Bayesian Opponent Modeling and Moral Rhetoric Framing for GLEE
Paper recorded by Signals 4 on 2026-10-27 in cs.CL. Abstract reproduced from arXiv; link to the original below.
Published 2026-10-27 on arXiv · recorded by Signals 4 on 2026-10-28
Category: cs.CL · 自然语言处理 · first seen 2026-10-28
Abstract
We describe the agent we submitted to the GLEE Competition, which plays bargaining, negotiation, and persuasion games against a shared pool of human and AI opponents. The agent is built around three central components: a classical game-theoretic solver to compute numeric moves, an online Bayesian layer to estimate opponent archetypes, and a language model to write accompanying messages. We utilize
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Cite this page: Game-Theoretic Solvers with Bayesian Opponent Modeling and Moral Rhetoric Framing for GLEE: the #128 most recent of 660 cs.CL papers we have recorded (as of 2026-10-27). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/game-theoretic-solvers-with-bayesian-opponent-modeling-and-moral-rhetoric-framin.html
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