Risk-Adaptive Behavioral Attenuation via Episode-Latched Policy Gating and Bounded Relearning for Deployed Reinforcement Learning Agents
Reinforcement learning behaviors can become harmful after deployment even when the policy is unchanged, a risk existing methods address mainly before or during training rather than through reversible correction. This paper proposes a risk-adaptive attenuation framework for a frozen context-conditioned policy encoding v...
Mehdi Samieiyeganeh, Tahir Mehmood, Parisa Bahraminikoo et al.
· Computers · 0 citations