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Found 4 papers, 3 papers with code
MSVIPER: Improved Policy Distillation for Reinforcement-Learning-Based Robot Navigation
Moreover, we present efficient policy distillation and tree-modification techniques that take advantage of the decision tree structure to allow improvements to a policy without retraining.
XAI-N: Sensor-based Robot Navigation using Expert Policies and Decision Trees
In order to increase the reliability and handle the failure cases of the expert policy, we combine with a policy extraction technique to transform the resulting policy into a decision tree format.
Conservative Q-Improvement: Reinforcement Learning for an Interpretable Decision-Tree Policy
There is a growing desire in the field of reinforcement learning (and machine learning in general) to move from black-box models toward more "interpretable AI."
The Impact of Humanoid Affect Expression on Human Behavior in a Game-Theoretic Setting
In this pilot study, we investigate (1) in what way a robot can express a certain mood to influence a human's decision making behavioral model; (2) how and to what extent the human will be influenced in a game theoretic setting.
