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On the role of planning in model-based deep reinforcement learning
Model-based planning is often thought to be necessary for deep, careful ...
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Exploring Exploration: Comparing Children with RL Agents in Unified Environments
Research in developmental psychology consistently shows that children ex...
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Divide-and-Conquer Monte Carlo Tree Search For Goal-Directed Planning
Standard planners for sequential decision making (including Monte Carlo ...
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Combining Q-Learning and Search with Amortized Value Estimates
We introduce "Search with Amortized Value Estimates" (SAVE), an approach...
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Object-oriented state editing for HRL
We introduce agents that use object-oriented reasoning to consider alter...
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Structured agents for physical construction
Physical construction -- the ability to compose objects, subject to phys...
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Relational inductive biases, deep learning, and graph networks
Artificial intelligence (AI) has undergone a renaissance recently, makin...
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Relational inductive bias for physical construction in humans and machines
While current deep learning systems excel at tasks such as object classi...
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Generating Plans that Predict Themselves
Collaboration requires coordination, and we coordinate by anticipating o...
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Goal Inference Improves Objective and Perceived Performance in Human-Robot Collaboration
The study of human-robot interaction is fundamental to the design and us...
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Pragmatic-Pedagogic Value Alignment
For an autonomous system to provide value (e.g., to customers, designers...
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Metacontrol for Adaptive Imagination-Based Optimization
Many machine learning systems are built to solve the hardest examples of...
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