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Found 4 papers, 2 papers with code
Hierarchical Framework for Optimizing Wildfire Surveillance and Suppression using Human-Autonomous Teaming
Initial attack surveillance and suppression models have linked action spaces and objectives, making their optimization computationally challenging.
Entropy-regularized Point-based Value Iteration
However, model-based planners may be brittle under these types of uncertainty because they rely on an exact model and tend to commit to a single optimal behavior.
Decision Making in Non-Stationary Environments with Policy-Augmented Search
In this paper, we introduce \textit{Policy-Augmented Monte Carlo tree search} (PA-MCTS), which combines action-value estimates from an out-of-date policy with an online search using an up-to-date model of the environment.
Active teacher selection for reinforcement learning from human feedback
The HUB framework and ATS algorithm demonstrate the importance of leveraging differences between teachers to learn accurate reward models, facilitating future research on active teacher selection for robust reward modeling.
