How do AI agents adapt to dynamic environments?

AI agents adapt to dynamic environments through continuous learning and self-improvement. They use techniques like online learning, where models are updated incrementally based on new data, and reinforcement learning, where agents adjust their strategies based on feedback from the environment. To handle changing conditions, AI agents often rely on predictive models that anticipate future states. In multi-agent systems, agents must also adapt to interactions with other agents, learning from their behaviors and adjusting accordingly for better coordination or competition.


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