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Most prior methods for learning navigation policies require access to simulation environments, as they need online policy interaction and rely on ground-truth maps for rewards.
Cognitive maps in rats and men
Edward C Tolman · 1948
Earlier work this paper cites.
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Ranxiao Frances Wang and Elizabeth S Spelke · 2002
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Do humans integrate routes into a cognitive map? map-versus landmark-based navigation of novel shortcuts
Patrick Foo, William H Warren, Andrew Duchon, and Michael J Tarr · 2005
Earlier work this paper cites.
Clustering by passing messages between data points
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Earlier work this paper cites.
Active learning from demonstration for robust autonomous navigation
David Silver, J Andrew Bagnell, and Anthony Stentz · 2012
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Target-driven visual navigation in indoor scenes using deep reinforcement learning
Yuke Zhu, Roozbeh Mottaghi, Eric Kolve, Joseph J Lim, Abhinav Gupta, Li Fei-Fei, and Ali Farhadi · 2017
Earlier work this paper cites.
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Earlier work this paper cites.
The cognitive map in humans: spatial navigation and beyond
Russell A Epstein, Eva Zita Patai, Joshua B Julian, and Hugo J Spiers · 2017
Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Angel Chang, Angela Dai, Thomas Funkhouser, Maciej Halber, Matthias Niessner, Manolis Savva, Shuran Song, Andy Zeng, and Yinda Zhang · 2017
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Dd-ppo: Learning near-perfect pointgoal navigators from 2.5 billion frames
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Sparse graphical memory for robust planning
Scott Emmons, Ajay Jain, Michael Laskin, Thanard Kurutach, Pieter Abbeel, and Deepak Pathak · 2020
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Ving: Learning open-world navigation with visual goals
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Semantic visual navigation by watching youtube videos
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Fei Xia, Amir R Zamir, Zhiyang He, Alexander Sax, Jitendra Malik, and Silvio Savarese · 2018
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Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, et al · 2019
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Fast graph representation learning with PyTorch Geometric
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Occupancy anticipation for efficient exploration and navigation
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Zero-shot imitation learning from demonstrations for legged robot visual navigation
Xinlei Pan, Tingnan Zhang, Brian Ichter, Aleksandra Faust, Jie Tan, and Sehoon Ha · 2020
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Keep doing what worked: Behavioral modelling priors for offline reinforcement learning
Noah Y Siegel, Jost Tobias Springenberg, Felix Berkenkamp, Abbas Abdolmaleki, Michael Neunert, Thomas Lampe, Roland Hafner, Nicolas Heess, and Martin Riedmiller · 2020
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Offline reinforcement learning: Tutorial, review, and perspectives on open problems
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Conservative q-learning for offline reinforcement learning
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Learning to plan with uncertain topological maps
Edward Beeching, Jilles Dibangoye, Olivier Simonin, and Christian Wolf · 2020
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Memory-augmented reinforcement learning for image-goal navigation
Lina Mezghani, Sainbayar Sukhbaatar, Thibaut Lavril, Oleksandr Maksymets, Dhruv Batra, Piotr Bojanowski, and Karteek Alahari · 2021
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