Using Constraints and Process Algebra for Specification of First-Class Agent Interaction Protocols

  • Tim Miller
  • Peter McBurney
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4457)


Current approaches to multi-agent interaction involve specifying protocols as sets of possible interactions, and hard-coding decision mechanisms into agent programs in order to decide which path an interaction will take. This leads to several problems, three of which are particularly notable: hard-coding the decisions about interaction within an agent strongly couples the agent and the protocols it uses, which means a change to a protocol involves a changes in any agent that uses such a protocol; agents can use only the protocols that are coded into them at design time; and protocols cannot be composed at runtime to bring about more complex interactions. To achieve the full potential of multi-agent systems, we believe that it is important that multi-agent interaction protocols exist at runtime in systems as entities that can be inspected, referenced, composed, and shared, rather than as abstractions that emerge from the behaviour of the participants. We propose a framework, called \(\mathcal{RASA}\), which regards protocols as first-class entities. In this paper, we present the first step in this framework: a formal language for specification of agent interaction protocols as first-class entities, which, in addition to specifying the order of messages using a process algebra, also allows designers to specify the rules and consequences of protocols using constraints. In addition to allowing agents to reason about protocols at runtime in order to improve their the outcomes to better match their goals, the language allows agents to compose more complex protocols and share these at runtime.


Multiagent System Process Algebra Agent Interaction Interaction Protocol Protocol State 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Tim Miller
    • 1
  • Peter McBurney
    • 1
  1. 1.Department of Computer Science, The University of Liverpool, Liverpool, L69 7ZFUK

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