Put your money where your mouth is: Evaluating strategic planning and execution of llm agents in an auction arena
Recent advancements in Large Language Models (LLMs) showcase advanced reasoning,
yet NLP evaluations often depend on static benchmarks. Evaluating this necessitates …
yet NLP evaluations often depend on static benchmarks. Evaluating this necessitates …
LLM as a Mastermind: A Survey of Strategic Reasoning with Large Language Models
This paper presents a comprehensive survey of the current status and opportunities for
Large Language Models (LLMs) in strategic reasoning, a sophisticated form of reasoning …
Large Language Models (LLMs) in strategic reasoning, a sophisticated form of reasoning …
Efficacy of Language Model Self-Play in Non-Zero-Sum Games
Game-playing agents like AlphaGo have achieved superhuman performance through self-
play, which is theoretically guaranteed to yield optimal policies in competitive games …
play, which is theoretically guaranteed to yield optimal policies in competitive games …
Large model strategic thinking, small model efficiency: transferring theory of mind in large language models
As the performance of larger, newer Large Language Models continues to improve for
strategic Theory of Mind (ToM) tasks, the demand for these state-of-the-art models increases …
strategic Theory of Mind (ToM) tasks, the demand for these state-of-the-art models increases …
Policy Space Response Oracles: A Survey
In game theory, a game refers to a model of interaction among rational decision-makers or
players, making choices with the goal of achieving their individual objectives. Understanding …
players, making choices with the goal of achieving their individual objectives. Understanding …
Generative AI for Game Theory-based Mobile Networking
With the continuous advancement of network technology, various emerging complex
networking optimization problems opened up a wide range of applications utilizating of …
networking optimization problems opened up a wide range of applications utilizating of …
Utility-inspired Reward Transformations Improve Reinforcement Learning Training of Language Models
Current methods that train large language models (LLMs) with reinforcement learning
feedback, often resort to averaging outputs of multiple rewards functions during training. This …
feedback, often resort to averaging outputs of multiple rewards functions during training. This …
Enhancing Language Model Rationality with Bi-Directional Deliberation Reasoning
This paper introduces BI-Directional DEliberation Reasoning (BIDDER), a novel reasoning
approach to enhance the decision rationality of language models. Traditional reasoning …
approach to enhance the decision rationality of language models. Traditional reasoning …
Game-theoretic LLM: Agent Workflow for Negotiation Games
This paper investigates the rationality of large language models (LLMs) in strategic decision-
making contexts, specifically within the framework of game theory. We evaluate several state …
making contexts, specifically within the framework of game theory. We evaluate several state …
Mechanism Design for LLM Fine-tuning with Multiple Reward Models
Recent research on fine-tuning large language models (LLMs) through the aggregation of
multiple preferences has attracted considerable attention. However, the existing literature …
multiple preferences has attracted considerable attention. However, the existing literature …