1 citations · 1 across the 3 of their papers we have counts for
4 papers
Zero-Shot Coordination in Ad Hoc Teams with Generalized Policy Improvement and Difference Rewards
Rupal Nigam, Niket Parikh, Hamid Osooli +3
Real-world multi-agent systems may require ad hoc teaming, where an agent must coordinate with other previously unseen teammates to solve a task in a zero-shot manner. Prior work o…
S2Act: Simple Spiking Actor
Ugur Akcal, Seung Hyun Kim, Mikihisa Yuasa +6
Spiking neural networks (SNNs) and biologically-inspired learning mechanisms are attractive in mobile robotics, where the size and performance of onboard neural network policies ar…
Neuro-Symbolic Generation of Explanations for Robot Policies with Weighted Signal Temporal Logic
Mikihisa Yuasa, Ramavarapu S. Sreenivas, Huy T. Tran
Neural network-based policies have demonstrated success in many robotic applications, but often lack human-explanability, which poses challenges in safety-critical deployments. To…
On Generating Explanations for Reinforcement Learning Policies: An Empirical Study
Mikihisa Yuasa, Huy T. Tran, Ramavarapu S. Sreenivas
Understanding a \textit{reinforcement learning} policy, which guides state-to-action mappings to maximize rewards, necessitates an accompanying explanation for human comprehension.…