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Cognitive Abilities in Agents

  • Beatriz López
  • Susana Fernández
Part of the Whitestein Series in Software Agent Technologies and Autonomic Computing book series (WSSAT)

Abstract

The aim of this chapter is to describe the cognitive abilities deployed on agents and multi-agent systems by using examples from applications carried out by the authors. Particularly, the following agent abilities are reviewed: problem solving, memory, decision making and learning capabilities. These abilities, which involve most of the research done in Artificial Intelligence during decades of dealing with isolated agents, are revised in order to incorporate the interaction of agents in a multi-agent environment. The results of incorporating such capabilities to agents are the enhancement of the generality and flexibility of the systems.

Keywords

Cognitive Ability Multiagent System Planning Agent Multiple Criterion Decision Making Problem Deliberative Agent 
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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References

  1. [1]
    A. Aamodt and E. Plaza. Case-based reasoning: Foundational issues, methodological variations, and system approaches. Artificial Intelligence Communications, 7(1):39–59, 1994.Google Scholar
  2. [2]
    J. Bajo and J. Corchado. Multiagent architecture for monitoring the North-Atlantic carbon dioxide exchange rate. In XI edition of the International Conference of the Spanish Association for Artificial Intelligence (CAEPIA’05), Santiago de Compostela (Spain), volume LNAI 4177, pages 321–330. Springer Verlag, November 2005.Google Scholar
  3. [3]
    J. Bajo and J. Corchado. Evaluation and monitoring of the air-sea interaction using a cbr-agents approach. In 6th International Conference on Case Based Reasoning (ICCBR’05), Chicago, Illinois (USA), volume LNAI, 3620, pages 50–62. Springer Verlag, August 2006.Google Scholar
  4. [4]
    J. Bajo, J. Corchado, and L. Castillo. Running agents in mobile devices. In X IberoAmerican Conference on Artificial Intelligence (IBERAMIA’ 06), Burgos (Spain), volume LNAI 4140, pages 58–67. Springer Verlag, October 2006.Google Scholar
  5. [5]
    J. Bajo, Y. de Paz, J. de Paz, Q. Martín, and J. Corchado. A shopping mall multiagent systems. In 7th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL’06), Burgos (Spain), volume LNAI 4224, pages 1166–1173. Springer Verlag, November 2006.Google Scholar
  6. [6]
    S. Biundo, K. Myers, and K. Rajan, editors. Contingent Planning via Heuristic Forward Search with Implicit Belief States, 2005.Google Scholar
  7. [7]
    V. Botti, C. Carrascosa, V. Julian, and J. Soler. The ARTIS Agent Architecture: Modelling Agents in Hard Real-Time Environments, volume 1, pages 63–76. Springer Verlag, 1999.Google Scholar
  8. [8]
    R. Brafman and J. Hoffmann. Conformant planning via heuristic forward search: A new approach. In S. Koenig, S. Zilberstein, and J. Koehler, editors, Proceedings of the 14th International Conference on Automated Planning and Scheduling (ICAPS-04), 2004.Google Scholar
  9. [9]
    M. Bratman, D. Israel, and M. Pollack. Plans and resource-bounded practical reasoning. Computational Intelligence, 4:349–355, 1988.CrossRefGoogle Scholar
  10. [10]
    T. Calvo, G. Mayor, and R. e. Mesiar. Aggregation Operators: New Trends and Applications, volume 97 of Studies in Fuzziness and Soft Computing. Physica-Verlag, 2002.Google Scholar
  11. [11]
    C. Carrascosa, J. Bajo, V. Julian, J. Corchado, and V. Botti. Hybrid multi-agent architecture as a real-time problem-solving model. Expert Systems with Applications, 34(1):2–17, 2008.CrossRefGoogle Scholar
  12. [12]
    L. Castillo, E. Armengol, E. Onaindía, L. Sebastiá, J. González-Boticario, A. Rodríguez, S. Fernández, J. D. Arias, and D. Borrajo. Samap. An user-oriented adaptive system for planning tourist visits. Expert Systems With Applications, 2008.Google Scholar
  13. [13]
    A. Cimatti and M. Roveri. Conformant planning via model checking. In 5th European Conference on Planning: Recent Advances in AI Planning, volume 1809 of LNCS, pages 21–34, 1999.CrossRefGoogle Scholar
  14. [14]
    J. Corchado, J. Aiken, and J. Bajo. A CBR agent for monitoring the co2 exchange rate. In Petra Ferner (ed), Case-Based Reasoning on Signals and Images, pages 213–246. Springer Verlag (Studies in Computacional Science, 73), 2007.Google Scholar
  15. [15]
    J. Corchado, J. Bajo, Y. de Paz, and D. Tapia. Intelligent environment for monitoring Alzheimer patients, agent technology for health care. Decision Support Systems, pages In Press, Corrected Proof, Available online 8 May 2007.Google Scholar
  16. [16]
    J. Corchado and R. Laza. Constructing deliberative agents with case-based reasoning technology. International Journal of Intelligent Systems, 18(12):1227–1241, 2003.CrossRefGoogle Scholar
  17. [17]
    J. Corchado, J. Pavón, E. Corchado, and L. Castillo. Development of CBR-BDI agents: A tourist guide application. In Advances in Case Based Reasoning (ECCBR’04), Madrid (Spain), volume LNAI 3155, pages 547–559. Springer Verlag, August–September 2004.Google Scholar
  18. [18]
    M. de la Asuncion, L. Castillo, J. Fdez.-Olivares, O. García-Pérez, A. González, and F. Palao. Knowledge and plan execution management in planning fire fighting operations. Workshop on Planning and Scheduling: Bridging Theory to Practice. European Conference on Artificial Intelligence, 2004.Google Scholar
  19. [19]
    M. de Weerdt, A. ter Mors, and C. Witteveen. Multi-agent planning an introduction to planning and coordination. Technical report, Delft University of Technology, 2005.Google Scholar
  20. [20]
    M. M. de Weerdt. Plan coordination. In Proceedings of the Doctorial Consortium of the International Conferenence on AI Planning and Scheduling, pages 142–145, 2003.Google Scholar
  21. [21]
    M. Delgado, F. Herrera, E. Herrera-Viedma, and L. Martinez. Combining Numerical and Linguistic Information in Group Decision Making. Information Sciences, 107:177–194, 1998.CrossRefMathSciNetGoogle Scholar
  22. [22]
    B. Drabble and A. Tate. O Plan: A situated planning agent. In M. Ghallab and A. Milani, editors, New Directions in AI Planning, pages 247–260. IOS Press (Amsterdam), 1996.Google Scholar
  23. [23]
    J. Figueira, S. Greco, and M. e. Ehrgott. Multiple Criteria Decision Analysis:State of the Art Surveys, volume 78 of International Series in Operations Research and Management Science. Springer, 2005.Google Scholar
  24. [24]
    M. Fox, A. Gerevini, D. Long, and I. Serina. Plan stability: Replanning versus plan repair. Proceedings of the 16th International Conference on Automated Planning and Scheduling (ICAPS’06), pages 193–202, 2006.Google Scholar
  25. [25]
    M. Fox and D. Long. Hybrid STAN: Identifying and managing combinatorial optimization subproblems in planning. In IJCAI, pages 445–452, 2001.Google Scholar
  26. [26]
    M. Glez-Bedia, J. Corchado, E. Corchado, and C. Fyfe. Analytical model for constructing deliberative agents. Engineering Intelligent Systems, 3:173–185, 2002.Google Scholar
  27. [27]
    F. Herrera and E. Herrera-Viedma. Linguistic decision analysis: Steps for solving decision problems under linguistic information. Fuzzy Sets and Systems, 115:67–82, 2000.MATHCrossRefMathSciNetGoogle Scholar
  28. [28]
    M. Huhns and L. Stephens. Miultiagent systems and society of agents. In Multiagent SystemsA Modern Approach to Distributed Artificial Inteligence. G. Weiss (eds), 1999.Google Scholar
  29. [29]
    V. J. J. Inglada, C. C. Casamayor, M. R. Pedruelo, J. V. S. Bayona, and V. B. Navarro. SIMBA: An Approach for Real-Time Multi-agent Systems, volume 2504, pages 282–293. Springer Verlag, 2002.Google Scholar
  30. [30]
    D. Isern and A. Moreno. Distributed guideline-based health care system. In 4th International Conference on Intelligent Systems Design and Applications (ISDA-2004), pages 145–150, Budapest, Hungary, 2004. IEEE Press.Google Scholar
  31. [31]
    D. Isern, A. Valls, and A. Moreno. Learning the user’s preferences for multiple criteria ranking. In XIII Congreso Espanol sobre Tecnologías y Lógica Fuzzy (ESTYLF’06), pages 325–330, Ciudad Real, Spain, 2006.Google Scholar
  32. [32]
    D. Isern, A. Valls, and A. Moreno. Using aggregation operators to personalize agent-based medical services. In B. Gabrys, R. J. Howlett, and L. C. Jain, editors, Knowledge-Based Intelligent Information and Engineering Systems (KES06), volume 4252 of LNAI, pages 1256–1263, Bournemouth, UK, 2006. Springer Verlag.Google Scholar
  33. [33]
    S. Jiménez, A. Coles, and A. Smith. Planning in probabilistic domains using a deterministic numeric planner. In R. Qu, editor, Proceedings PLANSIG-06 Nottingham, UK, 2006.Google Scholar
  34. [34]
    L. Kramer and S. Smith. Maximizing availability: a commitment heuristic for oversubscribed scheduling problems. In J. K. S. Z. S. K. (Eds), editor, Proceeding of IGAPS’05, pages 272–280, Monterey, CA, USA, 2005. AAAI Press.Google Scholar
  35. [35]
    P. Langley. Cognitive architectures and general intelligent systems. AI Magazine, pages 33–44, Summer 2006.Google Scholar
  36. [36]
    I. Little and S. Thiébaux. Concurrent probabilistic planner in the GraphPlan framework. In Proceedings of the Sixteenth International Conference on Automated Planning and Scheduling (IGAPS’ 06), The English Lake District, Cumbria, UK, 2006.Google Scholar
  37. [37]
    B. López, C. Pous, J. Serena, and J. Piula. Cooperative case-based agents for acute stroke diagnosis. In EGAI Workshop on Agents Applied in Health Gare. Riva di Garda, Italia, 2006.Google Scholar
  38. [38]
    X. Luo and N. R. Jennings. A spectrum of compromise aggregation operators for multi-attribute decision making. Artificial Intelligence, 171:161–184, 2007. doi:10.1016/j.artint.2006.11.004.CrossRefMathSciNetGoogle Scholar
  39. [39]
    M. Minsky. The Society of Mind. Simon & Schuster, 1985.Google Scholar
  40. [40]
    T. Mitchell. Machine Learning. McGraw-Hill, 1997.Google Scholar
  41. [41]
    M. Montaner, B. Lopez, and J. L. de la Rosa. Developing trust in recommender agents. In First International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS’02), pages 304–305. Bologna, Italia, 2002.Google Scholar
  42. [42]
    M. Montaner, B. López, and J. L. de la Rosa. Improving case representation and casebased maintenance in recommender agents. In Lecture Notes in Computer Science (Artificial Intelligence) 2416, pages 234–148, 2002.Google Scholar
  43. [43]
    M. Montaner, B. Lopez, and J. L. de la Rosa. Opinion-based filtering through trust. In Lecture Notes in Computer Science (Artificial Intelligence) 2446, pages 164–178, 2002.Google Scholar
  44. [44]
    O. B. O. and D. Aberdeen. The factored policy gradient planner (ipc-06 version). In Proceedings of the Fifth International Planning Competition, June 2006.Google Scholar
  45. [45]
    H. Palacios and H. Geffner. Compiling uncertainty away: Solving conformant planning problems using a classical planner (sometimes). In Proc. 21st Nat. Conf. on Artificial Intelligence (AAAI-06), 2006.Google Scholar
  46. [46]
    S. Russell and P. Norvig. Artificial Intelligence. A Modern Approach (second edition). Prentice-Hall, 2003.Google Scholar
  47. [47]
    S. Sen and G. Weiss. Learning in multiagent systems. In Multiagent Systems-A Modern Approach to Distributed Artificial Inteligence. G. Weiss (eds), 1999.Google Scholar
  48. [48]
    D. Smith. Choosing objectives in over-subscription planning. In Proceeding of ICAPS-04, pages 393–401, Whistle, Canada, 2004.Google Scholar
  49. [49]
    L. Steels and P. Vogt. Grounding adaptive language games in robotic agents. In Proceedings of EGAL’ 97, pages 476–484, 1997.Google Scholar
  50. [50]
    R. Xu, P. Yuan-Cui, and X.-F. X. H.-T. Cui. Multi-agent planning system for spacecraft. In Proceeding of the International Conference on Machine Learning and Cybernetics (ICMLC’03, volume 4, pages 1995–1999, Xi-an, China, 2003.Google Scholar
  51. [51]
    R. R. Yager. On Ordered Weighted Averaging Aggregation. Operators in Multicriteria Decisionmaking. IEEE Transactions on Systems, Man and Cybernetics, 18:183–190, 1988.MATHCrossRefMathSciNetGoogle Scholar

Copyright information

© Birkhäuser Verlag Basel/Switzerland 2007

Authors and Affiliations

  • Beatriz López
    • 1
  • Susana Fernández
    • 2
  1. 1.University of GironaGironaSpain
  2. 2.University Carlos III of MadridLeganés, MadridSpain

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