PRIMA 2026

The vision for PRIMA 2026 is to chart a path "Beyond Traditional MAS" by fusing the rigorous foundations of conventional Multi-Agent Systems with the flexibility, adaptability, and context-awareness of Generative and Agentic AI (GAAI). As advanced AI models proliferate, the MAS community is at a critical juncture. Research is shifting from static agent design to the engineering of "Next-Generation Agent Systems"—complex ecosystems where LLM-based agents, traditional MAS components, and humans effectively coexist. PRIMA 2026 invites contributions that explore these new AI-driven possibilities while advancing the foundational disciplines essential for building robust, reliable, and beneficial agent societies.

• Foundations of MAS
  • Logic and Reasoning
    • Logics of agency, belief, knowledge, and intention
    • Norms, obligations, and deontic logic
    • Argumentation theory
    • Reasoning under uncertainty
  • Collaboration & Coordination
    • Multi-agent planning, teamwork, and coalition formation
    • Distributed problem-solving and optimization
    • Negotiation, trust and reputation, and commitments
    • Institutions, organizations, and normative systems
  • Algorithmic Game Theory
    • Auctions and mechanism design
    • Cooperative games (theory, analysis, computation)
    • Noncooperative games (theory, analysis, computation)
    • Behavioral game theory
  • Computational Social Choice
    • Voting theory and aggregation rules
    • Fair division and resource allocation
    • Matching theory (preference-based)
    • Participatory budgeting, communication, and distortion
• Systems and Learning
  • Generative and Agentic AI
    • Agents embodied with Large Language Models (LLMs)
    • LLM-based planning, reasoning, and agentic workflows
    • Coordination and cooperation of generative agents
    • Modeling and analysis of generative MAS
    • Verification, safety, and evaluation of agentic systems
  • Agent and Multi-Agent Learning
    • Reinforcement learning (multi-agent, distributed)
    • Evolutionary approaches
    • Machine learning in MAS
    • Learning for value alignment
  • Engineering Multi-Agent Systems
    • Agent-oriented software engineering
    • Interaction protocols, formal specification, and verification
    • Agent programming languages, middleware, and platforms
    • Testing, debugging, and deployed system case studies
  • Agent-Based Modeling and Simulation
    • Simulation languages and platforms
    • Artificial societies and virtual environments
    • Modeling emergent behavior
    • System dynamics
    • Application case studies (e.g., economics, society, ecology)
• Interaction and Society
  • Human-Agent Interaction
    • Adaptive personal assistants
    • Embodied conversational agents
    • Virtual characters and multimodal user interfaces
    • Human-robot interaction
    • Affective computing
  • Decentralized Paradigms & Applications
    • Cloud, edge, IoT, and cybersecurity
    • Robotics and multi-robot systems
    • Smart cities, transport, and logistics
    • Energy management
    • Healthcare, e-business, e-learning
    • Games and entertainment
    • Sustainability and resource management
  • Ethics, Society, and Governance
    • Explainable AI (XAI) and agent transparency
    • Ethics, fairness, and accountability of AI systems
    • AI and Democracy (e.g., deliberation, opinion formation, countering misinformation)
    • Multi-agent systems for social good
    • Governance and regulation of agent societies