Abstract
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.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
Keywords
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.
References
Anderson, J.R., Bothell, D., Byrne, M.D., Douglass, S., Lebiere, C., Qin, Y.: An integrated theory of the mind. Psychological Review 111(4), 1036–1060 (2004)
Bourque, P., Fairley, R.E. (eds.): SWEBOK 3.0: Guide to the Software Engineering Body of Knowledge, 3rd edn. IEEE, Piscataway (2014)
CISQ: CISQ Specifications for Automated Quality Characteristic Measures. Object Management Group (2012), http://it-cisq.org/wp-content/uploads/2012/09/CISQ-Specification-for-Automated-Quality-Characteristic-Measures.pdf
de Penning, L., d’Avila Garcez, A.S., Lamb, L.C., Meyer, J.-J.C.: Neural-Symbolic Cognitive Agents: Architecture, Theory and Application. In: Lomuscio, A., Scerri, P. (eds.) The 13th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2014), pp. 1621–1622. IFAAMAS, Paris (2014)
Department of Defense: JP 3-09.3, Close Air Support. Washington, DC, Department of Defense (2009)
Department of the Army: FM 2-22.3 (FM 34-52), Human Intelligence Collector Operations. Washington, DC, Department of the Army (2006)
Ferguson, I.A.: Touring Machines: Autonomous Agents with Attitudes. Computer 25(5), 51–55 (1992)
Fischer, K., Muller, J.P., Pischel, M.: InteRRaP: Unifying Control in a Layered Agent Architecture. German Research Center for Artificial Intelligence, Saarbrucken (1995), http://www.dfki.uni-sb.de/~pischel/interrap.html
Hauser, R., Clausing, D.: The House of Quality. Harvard Business Review 66, 63–73 (1988)
Huber, M.J., Kumar, S., Lisse, S.A., McGee, D.: Integrating Authority, Deontics, and Deontics and Communications within a Joint Intention Framework. In: Huhns, M., Shehory, O. (eds.) The 2007 International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2007). IFAAMAS, Honolulu (2007)
Huber, M.J., Kumar, S., McGee, D.: Toward a Suite of Performatives based upon Joint Intention Theory. In: The AAMAS 2004 Workshop on Agent Communication (AC 2004), New York, NY (2004)
ISO: ISO/IEC 25010:2011: Systems and software engineering – Systems and software Quality Requirements and Evaluation (SQuaRE) – System and software quality models ISO (2011)
Laird, J.E.: The Soar Cognitive Architecture. MIT Press, Cambridge (2012)
Lesser, V., Corkill, D.: Challenges for Multi-Agent Coordination Theory Based on Empirical Observations. In: Lomuscio, A., Scerri, P. (eds.) The 13th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2014), pp. 1157–1160. IFAAMAS, Paris (2014)
Parunak, H.V.D.: ‘Go to the Ant’: Engineering Principles from Natural Agent Systems. Annals of Operations Research 75, 69–101 (1997)
Van Dyke Parunak, H., Nielsen, P., Brueckner, S., Alonso, R.: Hybrid Multi-agent Systems: Integrating Swarming and BDI Agents. In: Brueckner, S.A., Hassas, S., Jelasity, M., Yamins, D. (eds.) ESOA 2006. LNCS (LNAI), vol. 4335, pp. 1–14. Springer, Heidelberg (2007)
Quist, M., Yona, G.: A novel robust algorithm for structure-preserving embedding of metric and nonmetric spaces. Journal of Machine Learning Research 5, 399–430 (2004)
Steinberg, A.N., Bowman, C.L.: Revisions to the JDL Data Fusion Model. In: Hall, D.L., Llinas, J. (eds.) Handbook of Multisensor Data Fusion, pp. 2.1–2.19. CRC Press, Boca Raton (2001)
Taylor, G., Quist, M., Hicken, A.: Acquiring Agent-based Models of Conflict from Event Data. In: IJCAI 2009. AAAI Press, Pasadena (2009)
Vesely, W., Stamatelatos, M., Dugan, J., Fragola, J., Minarick, J., Railsback III, J.: Fault Tree Handbook with Aerospace Applications. NASA, Washington, DC (2002), http://www.hq.nasa.gov/office/codeq/doctree/fthb.pdf
Wood, S.D., Zaientz, J.D., Beard, J., Fredriksen, R., Huber, M.: An Intelligent Interface-Agent Framework for Robotic Command and Control. In: The 2004 Command and Control Research and Technology Symposium, San Diego, CA (2004)
Wray, R.E., Jones, R.M.: An introduction to Soar as an agent architecture. In: Sun, R. (ed.) Cognition and Multi-agent Interaction: From Cognitive Modeling to Social Simulation, pp. 53–78. Cambridge University Press, Cambridge (2005)
Zaientz, J.D., Beard, J.: Using Knowledge-Based Interface Design Techniques to Support Visual Analytics. In: Workshop on Intelligent User Interfaces for Intelligence Analysis at IUI 2006, Sydney, Australia (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Van Dyke Parunak, H., Huber, M., Jones, R., Quist, M., Zaientz, J. (2014). CaFé: A Group Process to Rationalize Technologies in Hybrid AAMAS Systems. In: Dalpiaz, F., Dix, J., van Riemsdijk, M.B. (eds) Engineering Multi-Agent Systems. EMAS 2014. Lecture Notes in Computer Science(), vol 8758. Springer, Cham. https://doi.org/10.1007/978-3-319-14484-9_12
Download citation
DOI: https://doi.org/10.1007/978-3-319-14484-9_12
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-14483-2
Online ISBN: 978-3-319-14484-9
eBook Packages: Computer ScienceComputer Science (R0)