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Found 2 papers, 1 papers with code
Environment Design for Inverse Reinforcement Learning
Even with abundant data, current inverse reinforcement learning methods that focus on learning from a single environment can fail to handle slight changes in the environment dynamics.
Effects of Different Optimization Formulations in Evolutionary Reinforcement Learning on Diverse Behavior Generation
To that effect, this paper considers an existing evolutionary reinforcement learning framework which exploits multi-objective optimization as a way to obtain policies that succeed at behavior-related tasks as well as completing the main goal.
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