Learning social behavior

This paper discusses the challenges of learning to behave socially in the dynamic, noisy, situated and embodied mobile multi-robot domain. Using the methodology for synthesizing basis behaviors as a substrate for generating a large repertoire of higher-level group !Lnteractions, in this paper we describe how, given the substrate, greedy agents can learn social rules that benefit the group ',as a whole. We describe three sources of reinforcement and show their effectiveness in learning nongreedy social rules. We then demonstrate the learning approach on a group of four mobile robots learning to yield and share information in a foraging task.