arXiv Machine Learning
Aug 4
Humans Are More Diverse: Frontier LLMs Show Extreme Policies in Idealised AI Development Races
arXiv:2608. 01193v1 Announce Type: cross Abstract: An AI development race creates a multi-agent safety dilemma.
Large language models replicate and predict human cooperation across experiments in game theory
arXiv:2511. 04500v3 Announce Type: replace Abstract: Large language models (LLMs) are increasingly deployed as decision-making agents in high-stakes domains and as imitators of human behavior in the social and behavioral sciences.
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arXiv AI
Jun 30
Collective cooperation without individual fidelity in LLM agents
arXiv:2606. 30454v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as agents in simulations of social systems, yet it remains unclear when their behavior can be interpreted as a faithful proxy for human decision-making.
arXiv AI
Aug 3
Shall We Play a Game? Language Models for Open-ended Wargames
arXiv:2509. 17192v3 Announce Type: replace Abstract: LLM-based social simulations can make a generated transcript look like a single behavioral signal, but the model behind that transcript may be doing several different jobs: choosing what an actor says or does, deciding what happens after an action, or both.
arXiv AI
6d ago
Do LLMs Take Care of Their Own? Similarity Signals Can Induce Cooperation
arXiv:2608. 12125v1 Announce Type: cross Abstract: As LLM-based agents with user-instructed goals are becoming widely deployed, they increasingly encounter each other in strategic interactions, and face challenges of finding mutually beneficial outcomes.
arXiv AI
Jun 9
Payoff scaling shapes cooperation in LLM agents across languages
arXiv:2601. 19082v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly deployed as autonomous agents that negotiate, coordinate, and act on behalf of users.
arXiv AI
Aug 11
Persuasive and Compliant Tendencies Predict Group Decision-Making in Humans and Language Models
arXiv:2608. 08199v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly involved in group decision-making with other LLMs and humans.
arXiv AI
Jul 16
A Survey on Hypergame Theory: Modelling Misaligned Perceptions and Nested Beliefs for Multi-Agent Systems
arXiv:2507. 19593v3 Announce Type: replace Abstract: Classical game-theoretic models typically assume rational agents, complete information, and common knowledge of payoffs - assumptions that are often violated in real-world MAS characterized by uncertainty, misaligned perceptions, and nested beliefs.
arXiv Machine Learning
Jun 17
Tacit Coordination of Large Language Models
arXiv:2601. 22184v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly deployed in multi-agent settings that require coordination without communication, from human-AI interaction to safety-critical scenarios.
arXiv AI
Jun 17
Using Cognitive Models to Improve Language Model Simulation of Human Persuasion Games
arXiv:2606. 17657v1 Announce Type: new Abstract: People make decisions differently in strategic interactions.
arXiv Machine Learning
Jun 24
BehaviorBench: Benchmarking Foundation Models for Behavioral Science Tasks
arXiv:2606. 24162v1 Announce Type: cross Abstract: Foundation models have been increasingly applied to behavioral science domains such as psychology, sociology, and economics.
arXiv AI
Jul 7
Evaluating Generative Agents with Actions Grounded in Socially Distributed Task Environments using Incognita
arXiv:2607. 02975v1 Announce Type: new Abstract: Effective agency in social environments depends on when an agent seeks knowledge, when it acts, and whether its actions are justified by acquired information.
arXiv AI
1d ago
Beyond Asking: A Pipeline for Personalized Game Generation that Reads Players from Behavior
arXiv:2608. 16196v1 Announce Type: new Abstract: Personalized game generation requires inferring a player's abilities and behavioral style from how they play.