Robotic “Food” Chains: Externalization of State and Program for Minimal-Agent Foraging

Abstract

This paper describes experiments inspired by theoretical work on information invariants ([Donald 1995], [Donald et al 1994]), a means of comparison and a methodology for design of single- and multi-agent systems. Analysis reveals the environmental information that the systems assume and exploit, while the design methodology seeks to move information and processing into the “physical” environment and task mechanics. The approach raises the issue of agents actively recording information, or even “programs,” into the physical environment. This paper provides an example system that dynamically encodes information and “programs” into its physical environment.The second source of inspiration for this work is the natural phenomenon of ant pheromone trail formation, shown to involve agents with simple, local control that encode information into the environment to arrive at globally complex behavior. Analogously, our robotic system actively encodes information into its physical environment in order to reduce sensing, actuation, and computational requirements. Thus, “minimal” agents with local sensing and action form a system that dynamically and globally adapts to environmental changes. We discuss how moving information and “processing” into the shared physical environment improves our ability to generate complex global behaviors from simple locally interacting agents.