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Bridging the Imitation Gap by Adaptive Insubordination
Luca Weihs
, Unnat Jain
, Iou Jen Liu
, Jordi Salvador
,
Svetlana Lazebnik
, Aniruddha Kembhavi
,
Alexander Schwing
Electrical and Computer Engineering
Coordinated Science Lab
National Center for Supercomputing Applications (NCSA)
Siebel School of Computing and Data Science
Research output
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Chapter in Book/Report/Conference proceeding
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Keyphrases
Imitation
100%
Insubordination
100%
Reinforcement Learning
66%
Imitation Learning
50%
Teaching Agent
33%
Challenging Tasks
16%
Making Decisions
16%
Particle Environment
16%
Multi-agent
16%
Task Set
16%
Memorization
16%
Parallel Combination
16%
Reward-based
16%
Grid World
16%
Learning Loss
16%
Privileged Information
16%
Expert Supervision
16%
3D Simulator
16%
Computer Science
Reinforcement Learning
100%
multi agent
25%
Parallel Combination
25%