Select to Perfect: Imitating desired behavior from large multi-agent data

arXiv:2405.03735v1 Announce Type: new
Abstract: AI agents are commonly trained with large datasets of demonstrations of human behavior. However, not all behaviors are equally safe or desirable. Desired characteristics for an AI agent can be expressed by assigning desirability scores, which we assume are not assigned to individual behaviors but to collective trajectories. For example, in a dataset of vehicle interactions, these scores might relate to the number of incidents that occurred. We first assess the effect of each individual …

agent arxiv behavior cs.ai cs.lg cs.ma data multi-agent type