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An intelligent agent in AI is any system that perceives its environment through sensors, acts upon that environment through actuators, and selects actions to maximize the achievement of its goals according to a performance measure. The agent abstracts from raw data to beliefs or state estimates, chooses among alternative actions using a decision procedure (rule-based, search/planning, optimization, or learned policy), and updates itself as the environment changes. In practice, an intelligent agent comprises: (i) a perception module for state estimation, (ii) a knowledge or model component capturing transition and observation dynamics, (iii) a decision-making core that maps states to actions (reactively or via look-ahead), and (iv) a learning component that improves perception, models, or policies from experience. Key properties of agents include autonomy (behavior primarily determined by the agent’s own experience rather than direct human control), reactivity (timely response to percepts and exogenous changes), proactiveness (goal-directed behavior and initiative, e.g., planning ahead rather than only reacting), social ability (interaction and coordination with other agents or humans via protocols or ______ _____ _______ ___ ___.
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