Artificial Intelligence › Core AI ›

Multi-Agent Systems

3306 directly classified papers

Papers per year

Papers

Efficient Reinforcement Learning for Zero-Shot Coordination in Evolving Games AAAI 2026

AgentODRL: A Large Language Model-based Multi-agent System for ODRL Generation AAAI 2026

MARS: A Meta-Adaptive Reinforcement Learning Framework for Risk-Aware Multi-Agent Portfolio Management AAAI 2026

A3D: Adaptive Affordance Assembly with Dual-Arm Manipulation AAAI 2026

VirtualEnv: A Platform for Embodied AI Research AAAI 2026

Decidable Multi-agent Epistemic Planning: A Situation Calculus Approach AAAI 2026

Enhancing Strategy Logic with Procedural Rationality AAAI 2026

Rational Revision of Group Intentions AAAI 2026

Truth-Tracking Evaluation in Opinion-Based Argumentation AAAI 2026

HierSearch: A Hierarchical Enterprise Deep Search Framework Integrating Local and Web Searches AAAI 2026

MARS: Multi-Agent Adaptive Reasoning with Socratic Guidance for Automated Prompt Optimization AAAI 2026

MAPS: Multi-Agent Personality Shaping for Collaborative Reasoning AAAI 2026

Dimension-Aware Active Annotation for Aesthetic Perception via Multi-Agent Human–AI Collaboration AAAI 2026

Cross-Scale Collaboration between LLMs and Lightweight Sequential Recommenders with Domain-Specific Latent Reasoning AAAI 2026

Colonel Blotto with Battlefield Games AAAI 2026

Optimal Welfare in Noncooperative Network Formation Under Attack AAAI 2026

Computing Equilibrium Nominations in Presidential Elections AAAI 2026

Designing Truthful Mechanisms for Asymptotic Fair Division AAAI 2026

Existence of 2-EFX Allocations of Chores AAAI 2026

Fair Incentives for Early Arrival in 0-1 Cooperative Games AAAI 2026

On the Approximation Ratio of Optimal Fixed-Price Mechanisms for Single and Multi-Unit Bilateral Trade AAAI 2026

Edge-Binary Public Goods Games AAAI 2026

Scalable Solutions to Zero-Sum Partially Observable Stochastic Games Through Belief Aggregation with Approximation Guarantees AAAI 2026

Area-Optimal Control Strategies for Heterogeneous Multi-Agent Pursuit AAAI 2026

Learning in Zero-Sum Markov Games: Relaxing Strong Reachability and Mixing Time Assumptions AAAI 2026