Imitating Cost-Constrained Behaviors in Reinforcement Learning

arXiv:2403.17456v1 Announce Type: new
Abstract: Complex planning and scheduling problems have long been solved using various optimization or heuristic approaches. In recent years, imitation learning that aims to learn from expert demonstrations has been proposed as a viable alternative to solving these problems. Generally speaking, imitation learning is designed to learn either the reward (or preference) model or directly the behavioral policy by observing the behavior of an expert. Existing work in imitation learning and inverse reinforcement learning has focused …

abstract arxiv cost cs.ai cs.lg expert imitation learning learn optimization planning reinforcement reinforcement learning scheduling speaking type