A design process for adaptive behavior of situated agents

  • Authors:
  • Elke Steegmans;Danny Weyns;Tom Holvoet;Yolande Berbers

  • Affiliations:
  • AgentWise, DistriNet, Department of Computer Science, K.U.Leuven, Leuven, Belgium;AgentWise, DistriNet, Department of Computer Science, K.U.Leuven, Leuven, Belgium;AgentWise, DistriNet, Department of Computer Science, K.U.Leuven, Leuven, Belgium;AgentWise, DistriNet, Department of Computer Science, K.U.Leuven, Leuven, Belgium

  • Venue:
  • AOSE'04 Proceedings of the 5th international conference on Agent-Oriented Software Engineering
  • Year:
  • 2004

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Abstract

Engineering non-trivial open multi-agent systems is a challenging task. Our research focusses on situated multi-agent systems, i.e. systems in which agents are explicitly placed in an environment which agents can perceive and in which they can act. Situated agents do not use long-term planning to decide what action sequence should be executed, but select actions based on the locally perceived state of the world and limited internal state. To cope with change and dynamism of the system, situated agents must be able to adapt their behavior. A well-known family of agent architectures for adaptive behavior are free-flow architectures. However, building a free-flow architecture based on an analysis of the problem domain is a quasi-impossible job for non-trivial agents. To tackle the complexity of designing adaptive agent behavior based on a free-flow architecture, suitable abstractions are needed to describe and structure the agent behavior. The abstraction of a role is obviously essential in this respect. A modeling language is needed as well to model the behavior of the agents. We propose a statechart modeling language to support the design of roles for situated agents. In this paper we describe a design process for adaptive behavior of situated agents as part of a multi-agent oriented methodology. The design process integrates the abstraction of a role with a free-flow architecture. Starting from the results of analysis of the problem domain, the designer incrementally refines the model of the agent behavior. The resulting class diagram serves as a basis for implementation. We illustrate the subsequent design steps with a case study on controlling a collection of automated guided vehicles.