PHYRE
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About
PHYRE is a benchmark for physical reasoning that presents a series of classical mechanics puzzles in a 2D environment, aimed at developing sample-efficient learning algorithms. Each puzzle contains a starting configuration and a goal state that must be achieved by agents defining actions in the simulation, focusing on the interaction of different object types. The tool categorizes tasks into templates that help assess the generalization capabilities of AI agents in solving these puzzles. The system is designed to push forward advancements in intelligent agents' understanding and reasoning about physics.
Platform
Features
• 2d environment simulations
• encourages sample-efficient learning
• cross-template generalization assessment
• task templates for evaluation
• goal-oriented puzzle structure
• set of classical mechanics puzzles
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