• Corpus ID: 199668689

PHYRE: A New Benchmark for Physical Reasoning

  title={PHYRE: A New Benchmark for Physical Reasoning},
  author={Anton Bakhtin and Laurens van der Maaten and Justin Johnson and Laura Gustafson and Ross B. Girshick},
Understanding and reasoning about physics is an important ability of intelligent agents. [] Key Method We test several modern learning algorithms on PHYRE and find that these algorithms fall short in solving the puzzles efficiently. We expect that PHYRE will encourage the development of novel sample-efficient agents that learn efficient but useful models of physics. For code and to play PHYRE for yourself, please visit this https URL.
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Physical Reasoning
  • E. Davis
  • Biology
    Handbook of Knowledge Representation
  • 2008
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ShapeStacks: Learning Vision-Based Physical Intuition for Generalised Object Stacking
This paper provides ShapeStacks, a simulation-based dataset featuring 20,000 stack configurations composed of a variety of elementary geometric primitives richly annotated regarding semantics and structural stability, and trains visual classifiers for binary stability prediction on the data and scrutinise their learned physical intuition.
Do New Caledonian crows solve physical problems through causal reasoning?
It is suggested that New Caledonian crows can solve complex physical problems by reasoning both causally and analogically about causal relations, and may form the basis of the NewCaledonian crow's exceptional tool skills.
CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning
This work presents a diagnostic dataset that tests a range of visual reasoning abilities and uses this dataset to analyze a variety of modern visual reasoning systems, providing novel insights into their abilities and limitations.