State-based representations are models that capture the current status or condition of a system at a specific moment in time, often used in the context of robotics and evolutionary algorithms. These representations are crucial for guiding the behavior and decision-making processes of robots, enabling them to respond dynamically to their environments. By focusing on the state of a system, these representations allow for more effective problem-solving and adaptation in complex tasks.
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