In artificial intelligence, symbolic world models bridge raw perception and logical reasoning by representing knowledge as structured symbols and rules. They enable AI to simulate scenarios, plan actions, and explain decisions transparently. Robotics, automated planning, and cognitive science benefit most, using these models for reliable navigation, complex problem-solving, and human-interpretable AI systems. This approach enhances adaptability and trust in dynamic environments.
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