Recent advances in the Multi-Agent Systems (MAS) field have generated optimism that widely applicable solutions to large, distributed problems may be at hand. However, before the field can deliver on that promise, the challenge of how to control such systems to address a pre-specified goal (e.g., minimize throughput of packets in data routing, win the game in soccer) in a decentralized, adaptive manner with minimal detailed hand-tuning needs to be met.
In this workshop we focus on two crucial properties that would allow a MAS to meet those challenges:
The importance of the second property lies in how the agents interact with one another and the environment. Because both the environment and the response of other agents to changes in that environment will modify the "background" state one agent perceives before choosing its actions, it is imperative that adaptivity be built in to those agents. Without this flexibility, only detailed hand-tailoring (an option not available in most large, interesting problems) will provide satisfactory behavior. Furthermore, the interaction structure among the agents needs to be adaptive, to allow the agents to fully exploit opportunities in a changing environment (e.g., form/dissolve teams).
There are many fields that have addressed aspects of these issues, including economics, and game theory. However, there are major differences in both the approach such fields take, and the set of assumptions that form the basis of those fields. For example, the components of a multi-agent system have many degrees of freedom that human beings do not. Due to this freedom, a MAS designer has a much larger "set of tools" than economists have. Furthermore, while game theory has established a strong theoretical basis for analyzing the equilibrium behavior of systems and how various equilibrium states relate to one another, there is little work on off-equilibrium behavior.
Therefore, neither the direct application, nor the simple extension of principles borrowed from those fields are likely to provide the theoretical underpinnings of teamwork and adaptivity in multi-agent systems. Our focus in this workshop will be to address the design of systems that are intended to solve large distributed computational problems with little to no handtailoring through the collective and adaptive behavior of the agents comprising that system.
Direct all questions and inquiries to the co-chairs:
AT&T Labs -- Research
180 Park Ave.
Florham Park, NJ 07932
phone: (973) 360-8333
fax : (973) 360-8970
NASA Ames Research Center
Mail Stop 269-4
Moffett Field, CA 94035-1000
phone: (650) 604-4940
fax : (650) 604-3594