The Effectiveness Of Transferring Multi-Agent Behaviors From A Learning Environment In The Presence Of Synthetic Social Features

The diverse behavior representation schemes and learning paradigms being investigated within the robotics community share the common feature that successful deployment of agents requires that behaviors developed in a learning environment are successfully applied to a range of unfamiliar and potentially more complex operational environments. The intent of our research is to develop insight into the factors facilitating successful transfer of behaviors to the operational environments. We present experimental results investigating the effects of several factors for a simulated swarm of autonomous vehicles. Our primary focus is on the impact of Synthetic Social Structures, which are guidelines directing the interactions between agents, much like social behaviors direct interactions between group members in the human and animal world. The social structure implemented is a dominance hierarchy, which has been shown previously to facilitate negotiation between agents. The goal of this investigation is to investigate mechanisms adding robustness to agent behavior. Copyright © 2005 by ASME