[논문리뷰] Code-Space Response Oracles: Generating Interpretable Multi-Agent Policies with Large Language ModelsarXiv에 게시된 'Code-Space Response Oracles: Generating Interpretable Multi-Agent Policies with Large Language Models' 논문에 대한 자세한 리뷰입니다.#Review#Multi-Agent Reinforcement Learning#Policy-Space Response Oracles#Large Language Models#Program Synthesis#Interpretable AI#Game Theory#Code Generation2026년 3월 11일댓글 수 로딩 중
[논문리뷰] Discovering Multiagent Learning Algorithms with Large Language ModelsarXiv에 게시된 'Discovering Multiagent Learning Algorithms with Large Language Models' 논문에 대한 자세한 리뷰입니다.#Review#Multi-Agent Reinforcement Learning#Game Theory#Large Language Models#Evolutionary Algorithms#Counterfactual Regret Minimization#Policy Space Response Oracles#Algorithm Discovery2026년 2월 19일댓글 수 로딩 중
[논문리뷰] Monopoly Deal: A Benchmark Environment for Bounded One-Sided Response Gamescavaunpeu이 arXiv에 게시한 'Monopoly Deal: A Benchmark Environment for Bounded One-Sided Response Games' 논문에 대한 자세한 리뷰입니다.#Review#Bounded One-Sided Response Games (BORGs)#Monopoly Deal#Benchmark Environment#Counterfactual Regret Minimization (CFR)#Imperfect Information Games#Game Theory#Self-Play#State Abstraction2025년 11월 9일댓글 수 로딩 중
[논문리뷰] GTAlign: Game-Theoretic Alignment of LLM Assistants for Mutual WelfarearXiv에 게시된 'GTAlign: Game-Theoretic Alignment of LLM Assistants for Mutual Welfare' 논문에 대한 자세한 리뷰입니다.#Review#Large Language Models#LLM Alignment#Game Theory#Reinforcement Learning#Mutual Welfare#Payoff Matrix#Strategic Decision Making#Human-AI Interaction2025년 10월 13일댓글 수 로딩 중
[논문리뷰] Multiplayer Nash Preference OptimizationarXiv에 게시된 'Multiplayer Nash Preference Optimization' 논문에 대한 자세한 리뷰입니다.#Review#RLHF#LLM Alignment#Nash Equilibrium#Multiplayer Games#Preference Optimization#Non-transitive Preferences#Game Theory2025년 9월 30일댓글 수 로딩 중