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The Cartographer
Repeated Inverse Reinforcement Learning
May 15, 2017 Β· Declared Dead Β· π Neural Information Processing Systems
"No code URL or promise found in abstract"
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Authors
Kareem Amin, Nan Jiang, Satinder Singh
arXiv ID
1705.05427
Category
cs.AI: Artificial Intelligence
Cross-listed
cs.LG
Citations
78
Venue
Neural Information Processing Systems
Last Checked
3 months ago
Abstract
We introduce a novel repeated Inverse Reinforcement Learning problem: the agent has to act on behalf of a human in a sequence of tasks and wishes to minimize the number of tasks that it surprises the human by acting suboptimally with respect to how the human would have acted. Each time the human is surprised, the agent is provided a demonstration of the desired behavior by the human. We formalize this problem, including how the sequence of tasks is chosen, in a few different ways and provide some foundational results.
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