Multi-Agent AI refers to systems where multiple autonomous agents interact, collaborate, or compete to achieve individual or shared goals. Each agent operates with its own perception, decision-making, and action capabilities, often using machine learning to adapt to dynamic environments. These agents can communicate, coordinate tasks, and solve complex problems more efficiently than single-agent systems. Multi-Agent AI is widely applied in robotics, simulations, gaming, traffic management, and distributed problem-solving. https://www.youngurbanproject.com/multi-agent-ai/

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A Learning Agent in AI is a type of intelligent system that improves its performance over time by learning from experience. It consists of key components: a learning element, performance element, critic, and problem generator. The learning element adapts based on feedback, while the performance element makes decisions. Learning agents are widely used in applications like robotics, game playing, and recommendation systems. https://www.youngurbanproject.....com/learning-agent-i