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Miroslav Olšák

2 accepted papers

2021

Planning from Pixels in Environments with Combinatorially Hard Search Spaces

NeurIPS 2021poster

The ability to form complex plans based on raw visual input is a litmus test for current capabilities of artificial intelligence, as it requires a seamless combination of visual processing and abstract algorithmic execution, two traditionally separate areas of computer science. A recent surge of int…

Cited by 8SourcePDFScholar
2018

Reinforcement Learning of Theorem Proving

NeurIPS 2018poster

We introduce a theorem proving algorithm that uses practically no domain heuristics for guiding its connection-style proof search. Instead, it runs many Monte-Carlo simulations guided by reinforcement learning from previous proof attempts. We produce several versions of the prover, parameterized by…