4 accepted papers
Task allocation in multi-human multi-robot (MHMR) teams presents significant challenges due to the inherent heterogeneity of team members, the dynamics of task execution, and the information uncertainty of operational states. Existing approaches often fail to address these challenges simultaneously,
Trust is essential in human-robot collaboration, particularly in multi-human, multi-robot (MH-MR) teams, where it plays a crucial role in maintaining team cohesion in complex operational environments. Despite its importance, trust is rarely incorporated into task allocation and reallocation algorith
Preference-based reinforcement learning (PbRL) is emerging as a promising approach to teaching robots through human comparative feedback without complex reward engineering. However, the substantial volume of human feedback required hinders broader applications. In this work, we introduce PrefCLM, a
LLMs are increasingly fine-tuned using RLHF datasets to align them with human preferences and values. However, very limited research has investigated which specific human values are operationalized through these datasets. In this paper, we introduce Value Imprint, a framework for auditing and classi…