Projected Task-Specific Layers for Multi-Task Reinforcement Learning

arXiv:2309.08776v2 Announce Type: replace
Abstract: Multi-task reinforcement learning could enable robots to scale across a wide variety of manipulation tasks in homes and workplaces. However, generalizing from one task to another and mitigating negative task interference still remains a challenge. Addressing this challenge by successfully sharing information across tasks will depend on how well the structure underlying the tasks is captured. In this work, we introduce our new architecture, Projected Task-Specific Layers (PTSL), that leverages a common policy with dense …

abstract arxiv challenge cs.ai cs.lg cs.ro homes however information interference manipulation negative reinforcement reinforcement learning robots scale tasks type will