From the 1 of 8 linked papers with an AI index.
8 papers
Communicating Chess Strategies in Natural Language
Langyuan Cui, Chun Kai Ling, Hwee Tou Ng
The paper introduces a task for verbalizing chess strategies in natural language, presenting a pipeline to generate such descriptions and an evaluation framework to assess them, de…
Enhancing Decision-Making with Large Language Models through Multi-Agent Fictitious Play
Leyang Shen, Yang Zhang, Xiaoyan Zhao +2
Large language model (LLM)-based multi-agent systems (MAS) have demonstrated great potential in solving tasks with execution complexity, by distributing subtasks across cooperative…
Equilibrium Computation in Extensive-Form Games with Stochastic Action Sets
Thomas Schwarz, Ryann Sim, Chun Kai Ling
Extensive-form games (EFGs) are a standard model for sequential decision-making in games. A fundamental and typically implicit assumption in EFGs is that players always have access…
CARL: Criticality-Aware Agentic Reinforcement Learning
Leyang Shen, Yang Zhang, Chun Kai Ling +2
Agents capable of accomplishing complex tasks through multiple interactions with the environment have emerged as a popular research direction. However, in such multi-step settings,…
Computing Equilibria in Games with Stochastic Action Sets
Thomas Schwarz, Jiaru Li, Ryann Sim +1
The study of learning in games typically assumes that each player always has access to all of their actions. However, in many practical scenarios, players' available actions might…
Game of Thought: Robust Information Seeking with Large Language Models Using Game Theory
Langyuan Cui, Chun Kai Ling, Hwee Tou Ng
Large Language Models (LLMs) are increasingly deployed in real-world scenarios where they may lack sufficient information to complete a given task. In such settings, the ability to…