agenttheory

Agent theory is a multidisciplinary field that studies agents—entities capable of perceiving their environment, deliberating, and taking actions to achieve goals. It encompasses philosophy, cognitive science, artificial intelligence, economics, and robotics, and provides conceptual and formal tools for analyzing agency and intentional behavior.

Its central concerns include the internal states of agents (beliefs, desires, and intentions in the BDI tradition), their autonomy and adaptivity, the nature of rational action, and how agents interact with environments and with each other. Formal models used in agent theory include belief-desire-intention (BDI) frameworks, decision-theoretic approaches such as Markov decision processes and partially observable MDPs, and game-theoretic analyses for multi-agent contexts. Agents are often classified by architecture (reactive vs deliberative vs hybrid) and by scope (single-agent vs multi-agent systems).

Applications span autonomous robotics and control, simulation and training, e-commerce and online markets, distributed AI, and policy design where agent-based models are used to study complex systems. Research topics include agent learning and adaptation, multi-agent coordination, negotiation and communication protocols, safety, and alignment with human values.

Critiques focus on limits of rationality, computational feasibility, and representational assumptions; ethics and governance concerns arise as autonomous agents perform high-stakes tasks. See also related topics in artificial intelligence, multi-agent systems, planning, and decision theory.