Search Results for author:
Found 4 papers, 3 papers with code
Scalable Decision-Making in Stochastic Environments through Learned Temporal Abstraction
Notably, across tasks ranging from continuous control with inherently stochastic dynamics to high-dimensional robotic hand manipulation, L-MAP significantly outperforms existing model-based methods and performs on-par with strong model-free actor-critic baselines, highlighting the effectiveness of the proposed approach in planning in complex and stochastic environments with high-dimensional action spaces.
Multi-Agent Reinforcement Learning with Hierarchical Coordination for Emergency Responder Stationing
An emergency responder management (ERM) system dispatches responders, such as ambulances, when it receives requests for medical aid.
Multi-agent Reinforcement Learning
Reinforcement Learning (RL)
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we introduce \textit{Policy-Augmented Monte Carlo tree search} (PA-MCTS), which combines action-value estimates from an out-of-date policy with an online search using an up-to-date model of the environment.
Dynamic Simplex: Balancing Safety and Performance in Autonomous Cyber Physical Systems
To address these limitations, we propose a dynamic simplex strategy with an online controller switching logic that allows two-way switching.
