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Found 4 papers, 0 papers with code
Beyond Joint Demonstrations: Personalized Expert Guidance for Efficient Multi-Agent Reinforcement Learning
Multi-Agent Reinforcement Learning (MARL) algorithms face the challenge of efficient exploration due to the exponential increase in the size of the joint state-action space.
Enhancing Multi-Agent Coordination through Common Operating Picture Integration
Our results demonstrate the efficacy of COP integration, and show that COP-based training leads to robust policies compared to state-of-the-art Multi-Agent Reinforcement Learning (MARL) methods when faced with out-of-distribution initial states.
Insta-RS: Instance-wise Randomized Smoothing for Improved Robustness and Accuracy
Randomized smoothing (RS) is an effective and scalable technique for constructing neural network classifiers that are certifiably robust to adversarial perturbations.
Ray Space Features for Plenoptic Structure-From-Motion
In this paper, we explore using light fields captured by plenoptic cameras or camera arrays as inputs.
