MultiAgent

MultiAgent refers to the study and practice of systems composed of multiple autonomous agents that interact within a shared environment to achieve individual or collective goals. An agent is a software or hardware entity capable of perceiving its surroundings, making decisions, and acting to influence the environment. Agents may be cooperative, competitive, or both, and can range from simple rule-based controllers to sophisticated planning and learning systems. MultiAgent systems (MAS) are often distributed and operate without a central controller, which can enhance scalability and fault tolerance.

Key features of MultiAgent systems include autonomy, social ability, reactivity, and proactivity. Agents communicate using structured languages and protocols to negotiate, coordinate, and collaborate. Architectures span reactive, subsumption-based designs and deliberative approaches based on beliefs, desires, and intentions (BDI). Coordination and coordination mechanisms employ methods such as contract net protocols, auctions, voting, and consensus algorithms to assign tasks, resolve conflicts, and align goals among agents.

Common applications of MultiAgent systems appear in robotics, distributed sensor networks, traffic management, energy and resource allocation, supply chain optimization, and emergency response. MAS research often emphasizes scalability, robustness, adaptability, and interoperability across heterogeneous agents and environments.

Key challenges include achieving interoperability among diverse platforms, ensuring security and trust in interactions, verifying and explaining emergent system behavior, and managing complexity in large-scale deployments. Ongoing work explores learning within agents, swarm-inspired approaches, and the development of standards for agent communication and data exchange to enable reuse and integration across domains.