Update: This paper has been rejected :(. Time to address the reviewers' comments and get ready for IJCAI 09.
I just recently submitted a paper to the Eighth International Conference on Autonomous Agents and Multiagent Systems (AAMAS '09). The paper describes work done by myself and my adviser Dr. Marie desJardins and describes our current endeavors in swarm-level interactive control.
To make a long story short, this paper discusses the method of rule abstraction, which is used to define high-level properties of swarms that emerge out of low-level behaviors. We provide an example implementation of rule abstraction and apply it to two domains: agents that self-organize into circles (shown in the image in this post) and boid agents that flock.
Title: Learning Abstract Properties of Swarm Systems
Abstract:
Rule abstraction is an intuitive new tool that we propose for implementing and controlling swarm systems. The methods presented in this paper encourage a new paradigm for designing swarm applications: engineers can interact with a swarm at the abstract (swarm) level instead of the individual (agent) level. This is made possible by modeling and learning how particular abstract properties arise from low-level agent behaviors. In this paper, we present a procedure for building abstract properties and discuss how they can be used. We also provide experimental results showing that abstract rules can be learned through observation.
Link: Learning Abstract Properties of Swarm Systems by Don Miner and Marie desJardins
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