EVOLVING STRUCTURES FOR PREDICTIVE DECISION MAKING IN NEGOTIATIONS

Marisa Masvoula, Panagiotis Kanellis, Drakoulis Martakos

2010

Abstract

Predictive decision making increases the individual or joint gain of negotiators, and has been extensively studied. One particular skill of predicting agents is the forecast of their opponents’ future offers. Current systems focus on enhancing learning techniques in the decision making module of negotiating agents, with the purpose to develop more robust systems. Empirical studies are conducted in bounded problem spaces, where data distribution is known or assumed. Our proposal concentrates on the incorporation of learning structures in agents’ decision making, capable of forecasting opponents’ future offers even in open problem spaces, which is the case in most negotiation situations.

References

  1. Albesano, D., Gemello, R. Laface, P., Mana, F., Scanzio. S. (2006) Adaptation of Artificial Neural Networks Avoiding Catastrophic Forgetting. In Proceedings of IJCNN 2006 (pp. 1554-1561).
  2. Albesano, D., Gemello, R. Laface, P., Mana, F., Scanzio. S. (2006) Adaptation of Artificial Neural Networks Avoiding Catastrophic Forgetting. In Proceedings of IJCNN 2006 (pp. 1554-1561).
  3. Brzostowski, J. and Kowalczyk, R. (2006). Adaptive Negotiation with On-Line Prediction of Opponent Behaviour in Agent-Based Negotiations. In Proceedings of the IEEE/WIC/ACM international Conference on intelligent Agent Technology (pp. 263- 269). Washington, DC: IEEE Computer Society.
  4. Brzostowski, J. and Kowalczyk, R. (2006). Adaptive Negotiation with On-Line Prediction of Opponent Behaviour in Agent-Based Negotiations. In Proceedings of the IEEE/WIC/ACM international Conference on intelligent Agent Technology (pp. 263- 269). Washington, DC: IEEE Computer Society.
  5. Carbonneau, R., Kersten, G. E., and Vahidov, R. (2008). Predicting opponent's moves in electronic negotiations using neural networks. Expert Systems with Applications: An International Journal, 34 (2), 1266- 1273.
  6. Carbonneau, R., Kersten, G. E., and Vahidov, R. (2008). Predicting opponent's moves in electronic negotiations using neural networks. Expert Systems with Applications: An International Journal, 34 (2), 1266- 1273.
  7. Faratin, P., Sierra, C. and Jennings, N. R. (1998). Negotiation Decision Functions for Autonomous Agents. Int. Journal of Robotics and Autonomous Systems, 24 (3 - 4), 159-182.
  8. Faratin, P., Sierra, C. and Jennings, N. R. (1998). Negotiation Decision Functions for Autonomous Agents. Int. Journal of Robotics and Autonomous Systems, 24 (3 - 4), 159-182.
  9. Hou, C. (2004). Predicting Agents Tactics in Automated Negotiation. In Proceedings of the intelligent Agent Technology, IEEE/WIC/ACM international Conference (pp. 127-133). Washington, DC : IEEE Computer Society.
  10. Hou, C. (2004). Predicting Agents Tactics in Automated Negotiation. In Proceedings of the intelligent Agent Technology, IEEE/WIC/ACM international Conference (pp. 127-133). Washington, DC : IEEE Computer Society.
  11. Kasabov, N. (2007). Evolving Connectionist Systems: The Knowledge Engineering Approach. London: SpringerVerlag,
  12. Kasabov, N. (2007). Evolving Connectionist Systems: The Knowledge Engineering Approach. London: SpringerVerlag,
  13. Kersten, G. E, Chen, E., Neumann, D., Vahidov, R., Weinhardt, D. (2008). On Comparison of Mechanisms of Economic and Social Exchanges: The Times Model, Negotiation, Auctions and Market Engineering. Heidelberg: Springer Berlin.
  14. Kersten, G. E, Chen, E., Neumann, D., Vahidov, R., Weinhardt, D. (2008). On Comparison of Mechanisms of Economic and Social Exchanges: The Times Model, Negotiation, Auctions and Market Engineering. Heidelberg: Springer Berlin.
  15. Lee, C. C. and Ou-Yang, C. (2009). A neural networks approach for forecasting the supplier's bid prices in supplier selection negotiation process. Expert Systems with Applications, 36(2), 2961-2970
  16. Lee, C. C. and Ou-Yang, C. (2009). A neural networks approach for forecasting the supplier's bid prices in supplier selection negotiation process. Expert Systems with Applications, 36(2), 2961-2970
  17. Oprea, M. (2003) The Use of Adaptive Negotiation by a Shopping Agent in Agent-Mediated Electronic Commerce. In: Proceedings of the 3rd International Central and Eastern European Conference on MultiAgent Systems, CEEMAS03. (pp. 594-605). Heidelberg: Springer Berlin.
  18. Oprea, M. (2003) The Use of Adaptive Negotiation by a Shopping Agent in Agent-Mediated Electronic Commerce. In: Proceedings of the 3rd International Central and Eastern European Conference on MultiAgent Systems, CEEMAS03. (pp. 594-605). Heidelberg: Springer Berlin.
  19. Papaioannou, I. V., Roussaki, I. G., and Anagnostou, M. E. (2006). Comparing the Performance of MLP and RBF Neural Networks Employed by Negotiating Intelligent Agents. In Proceedings of the IEEE/WIC/ACM international Conference on intelligent Agent Technology (602-612). Washington, DC: IEEE Computer Society.
  20. Papaioannou, I. V., Roussaki, I. G., and Anagnostou, M. E. (2006). Comparing the Performance of MLP and RBF Neural Networks Employed by Negotiating Intelligent Agents. In Proceedings of the IEEE/WIC/ACM international Conference on intelligent Agent Technology (602-612). Washington, DC: IEEE Computer Society.
  21. Papaioannou, I., Roussaki, I., and Anagnostou, M. (2008). Detecting Unsuccessful Automated Negotiation Threads When Opponents Employ Hybrid Strategies. In D. Huang, D. C. Wunsch, D. S. Levine, and K. Jo, (Eds.), Proceedings of the 4th international Conference on intelligent Computing (pp. 27-39). Heidelberg: Springer Berlin.
  22. Papaioannou, I., Roussaki, I., and Anagnostou, M. (2008). Detecting Unsuccessful Automated Negotiation Threads When Opponents Employ Hybrid Strategies. In D. Huang, D. C. Wunsch, D. S. Levine, and K. Jo, (Eds.), Proceedings of the 4th international Conference on intelligent Computing (pp. 27-39). Heidelberg: Springer Berlin.
  23. Roussaki, I., Papaioannou, I., Anagnostou, M. (2007). Building Automated Negotiation Strategies Enhanced by MLP and GR Neural Networks for Opponent Agent Behaviour Prognosis. In Sandoval, F., Gonzalez Prieto, A., Cabestany, J., Grana, M. (eds.) IWANN 2007 (pp. 152-161) Heidelberg: Springer Berlin.
  24. Roussaki, I., Papaioannou, I., Anagnostou, M. (2007). Building Automated Negotiation Strategies Enhanced by MLP and GR Neural Networks for Opponent Agent Behaviour Prognosis. In Sandoval, F., Gonzalez Prieto, A., Cabestany, J., Grana, M. (eds.) IWANN 2007 (pp. 152-161) Heidelberg: Springer Berlin.
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Paper Citation


in Harvard Style

Masvoula M., Kanellis P. and Martakos D. (2010). EVOLVING STRUCTURES FOR PREDICTIVE DECISION MAKING IN NEGOTIATIONS . In Proceedings of the 12th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-8425-05-8, pages 391-394. DOI: 10.5220/0002895003910394


in Bibtex Style

@conference{iceis10,
author={Marisa Masvoula and Panagiotis Kanellis and Drakoulis Martakos},
title={EVOLVING STRUCTURES FOR PREDICTIVE DECISION MAKING IN NEGOTIATIONS},
booktitle={Proceedings of the 12th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2010},
pages={391-394},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002895003910394},
isbn={978-989-8425-05-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - EVOLVING STRUCTURES FOR PREDICTIVE DECISION MAKING IN NEGOTIATIONS
SN - 978-989-8425-05-8
AU - Masvoula M.
AU - Kanellis P.
AU - Martakos D.
PY - 2010
SP - 391
EP - 394
DO - 10.5220/0002895003910394