2.9k citations · 6k across the 15 of their papers we have counts for
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The StreetLearn Environment and Dataset
Piotr Mirowski, Andras Banki-Horvath, Keith Anderson +8
Navigation is a rich and well-grounded problem domain that drives progress in many different areas of research: perception, planning, memory, exploration, and optimisation in parti…
Learning to Navigate in Cities Without a Map
Piotr Mirowski, Matthew Koichi Grimes, Mateusz Malinowski +7
Navigating through unstructured environments is a basic capability of intelligent creatures, and thus is of fundamental interest in the study and development of artificial intellig…
Learning to Search with MCTSnets
Arthur Guez, Théophane Weber, Ioannis Antonoglou +5
Planning problems are among the most important and well-studied problems in artificial intelligence. They are most typically solved by tree search algorithms that simulate ahead in…
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
David Silver, Thomas Hubert, Julian Schrittwieser +10
The game of chess is the most widely-studied domain in the history of artificial intelligence. The strongest programs are based on a combination of sophisticated search techniques,…