3 papers
cs.LG2024
Markov Balance Satisfaction Improves Performance in Strictly Batch Offline Imitation Learning
Rishabh Agrawal, Nathan Dahlin, Rahul Jain +1
Imitation learning (IL) is notably effective for robotic tasks where directly programming behaviors or defining optimal control costs is challenging. In this work, we address a sce…
cs.LG2023
Conditional Kernel Imitation Learning for Continuous State Environments
Rishabh Agrawal, Nathan Dahlin, Rahul Jain +1
Imitation Learning (IL) is an important paradigm within the broader reinforcement learning (RL) methodology. Unlike most of RL, it does not assume availability of reward-feedback.…
cs.MA2022
Socially Intelligent Genetic Agents for the Emergence of Explicit Norms
Rishabh Agrawal, Nirav Ajmeri, Munindar P. Singh
Norms help regulate a society. Norms may be explicit (represented in structured form) or implicit. We address the emergence of explicit norms by developing agents who provide and r…