$\lambda$-models: Effective Decision-Aware Reinforcement Learning with Latent Models

arXiv:2306.17366v3 Announce Type: replace
Abstract: The idea of decision-aware model learning, that models should be accurate where it matters for decision-making, has gained prominence in model-based reinforcement learning. While promising theoretical results have been established, the empirical performance of algorithms leveraging a decision-aware loss has been lacking, especially in continuous control problems. In this paper, we present a study on the necessary components for decision-aware reinforcement learning models and we showcase design choices that enable well-performing algorithms. To this end, …

abstract algorithms arxiv continuous control cs.ai cs.lg decision lambda loss making performance reinforcement reinforcement learning results type