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cs.AI2024
RLZero: Direct Policy Inference from Language Without In-Domain Supervision
Harshit Sikchi, Siddhant Agarwal, Pranaya Jajoo +6
The reward hypothesis states that all goals and purposes can be understood as the maximization of a received scalar reward signal. However, in practice, defining such a reward sign…
cs.AI2024
Automated Discovery of Functional Actual Causes in Complex Environments
Caleb Chuck, Sankaran Vaidyanathan, Stephen Giguere +3
Reinforcement learning (RL) algorithms often struggle to learn policies that generalize to novel situations due to issues such as causal confusion, overfitting to irrelevant factor…