CaFé: A Group Process to Rationalize Technologies in Hybrid AAMAS Systems

  • H. Van Dyke Parunak
  • Marcus Huber
  • Randolph Jones
  • Michael Quist
  • Jack Zaientz
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8758)


Most agent research seeks insights about a single technology, and problems are chosen to allow this focus. In contrast, many real-world applications do not lend themselves to a single technology, but require multiple tools. In an applied AI company, each tool often has its own advocate, whose specialized knowledge may lead her to overestimate her tool’s contribution and diminish that of other tools. To form an effective team, the various members must have a shared understanding of how their tools complement one another. This paper describes CaFé (“Cases-Features”), a group process that we have prototyped for building a consensus mapping between tools and real-world problems. The five AI technologies encompassed in our prototype are cognitive architectures, intelligent user interfaces, classic multi-agent system paradigms, statistics and machine learning, and swarming. Structured group discussion identifies the dimensions of a feature space in which the technologies are distinct. The scheme that emerged from our exercise does not pretend to be an exhaustive characterization of the techniques, but it is a jointly owned map of our technology capabilities that has proven useful in design of new use cases.


Feature Space Multiagent System Software Quality Data Visualizer Cognitive Architecture 
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 International Publishing Switzerland 2014

Authors and Affiliations

  • H. Van Dyke Parunak
    • 1
  • Marcus Huber
    • 1
  • Randolph Jones
    • 1
  • Michael Quist
    • 1
  • Jack Zaientz
    • 1
  1. 1.Soar Technology, Inc.Ann ArborUSA

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