My research interests surround learning-based methods for simulation and control and include generative modelling, model-based reinforcement learning and character control.
Skill Transfer via Partially Amortized Hierarchical Planning
Kevin Xie*, Homanga Bharadhwaj*, Danijar Hafner, Animesh Garg, Florian Shkurti
Learning temporally extended skills for planning with a world model improves MBRL training and transfer.
ICLR, 2021 (to appear) paper website
Continual Model-Based Reinforcement Learning with Hypernetworks
Philip Huang, Kevin Xie, Homanga Bharadhwaj, Florian Shkurti
Task-conditioned hypernetworks continually adapt to change in environment dynamics with a limited replay buffer.
Deep RL Workshop (NeurIPS), 2020 paper
Model-Predictive Planning via Cross-Entropy and Gradient-Based Optimization
Homanga Bharadhwaj*, Kevin Xie*, Florian Shkurti,
Updating the top action sequences identified by CEM through a few gradient steps helps improve sample efficiency and performance of planning in Model-based RL.
L4DC, 2020 paper
Progressive Reinforcement Learning with Distillation for Multi-Skilled Motion Control
Glen Berseth*, Kevin Xie*, Paul Cernek, Michiel van de Panne
Progressive learning and integration via distillation (PLAID) allows a single policy to quickly acquire new locomotion skills.
ICLR, 2018 arXiv