IDIL: Imitation Learning of Intent-Driven Expert Behavior

arXiv:2404.16989v1 Announce Type: new
Abstract: When faced with accomplishing a task, human experts exhibit intentional behavior. Their unique intents shape their plans and decisions, resulting in experts demonstrating diverse behaviors to accomplish the same task. Due to the uncertainties encountered in the real world and their bounded rationality, experts sometimes adjust their intents, which in turn influences their behaviors during task execution. This paper introduces IDIL, a novel imitation learning algorithm to mimic these diverse intent-driven behaviors of experts. Iteratively, …

abstract arxiv behavior cs.ai cs.lg cs.ro decisions diverse expert experts human imitation learning type unique world