![](bg6.png)
1
0,2
0
0,1
0,3
0,4
0,5
0,6
0,7
0,8
1
0,9
2
3
4
5
6
78
Utility
Interactions
tneSslasoporP
devieceRslasoporP
Average Utility of Seller
Figure 3: Before, without machine learning.
1
0,2
0
0,1
0,3
0,4
0,5
0,6
0,7
0,8
1
0,9
2
3
4
5
6
78
Utility
Interactions
tneSslasoporP
devieceRslasoporP
Average Utility of Seller
Figure 4: After, with machine learning.
6 FINAL REMARKS
This paper has presented a novel approach by propos-
ing a software framework for supporting adaptive bi-
lateral negotiation. The major contribution of this pa-
per is the proposed decision making apparatus. To
model opponent players, an algorithm that uses self-
organizing maps (neural networks) and a Q-Learning
algorithm used basically to predicting the next im-
portant actions were proposed. Therefore, some im-
provements over current existing approaches include
the combination of neural networks and Q-Learning,
used in an appropriated software framework.
For future work, is aimed to develop new com-
ponents that implement other artificial intelligence
techniques in order to be compared with the exist-
ing ones. For example, case-based learning to be
compared with neural networks with regard to play-
ers modelling.
REFERENCES
Bartolini, C., Preist, C., and Jennings, N. R. (2004). A
Software Framework for Automated Negotiation. In
Choren, R., Garcia, A., Lucena, C., and Romanovsky,
A., editors, Software Engineering for Large-Scale
Multi-Agent Systems, volume 3390 of Lecture Notes in
Computer Science, pages 213–235. Springer-Verlag.
Bianchi, R. A. C., Ribeiro, C. H. C., and Costa, A. H. R.
(2004). Heuristically accelerated q-learning: A new
approach to speed up reinforcement learning. In Baz-
zan, A. L. C. and Labidi, S., editors, 17th Brazilian
Symposium on Artificial Intelligence, volume 3171 of
Lecture Notes in Computer Science, pages 245–254.
Springer.
Debenham, J. K. (2003). An eNegotiation Framework.
In Australian Conference on Artificial Intelligence,
pages 833–846.
Faratin, P., Sierra, C., and Jennings, N. R. (2002). Us-
ing Similarity Criteria to Make Issue Trade-offs
in Automated Negotiations. Artificial Intelligence,
142(2):205–237.
Fatima, S. S., Wooldridge, M., and Jennings, N. R. (2004).
An Agenda Based Framework for Multi-issues Nego-
tiation. Artificial Intelligence, 152(1):1–45.
Filho, R. R. G. N. and Costa, E. B. (2003). A Decision-
Making Model to Support Negotiation in Electronic
Commerce. In 3rd International Interdisciplinary
Conference on Electronic Commerce (ECOM-03),
pages 16–18, Gdansk, Poland.
Jennings, N. R., Faratin, P., Lomuscio, A. R., Parsons,
S., Wooldridge, M., and Sierra, C. (2001). Au-
tomated Negotiation: Prospects Methods and Chal-
lenges. Group Decision and Negotiation, 10(2):199–
215.
Klein, M., Faratin, P., Sayama, H., and Bar-Yam, Y. (2003).
Protocols for Negotiating Complex Contracts. IEEE
Intelligent Systems, 18(6):32–38.
Narayanan, V. and Jennings, N. R. (2005). An adap-
tive bilateral negotiation model for e-commerce set-
tings. In Seventh IEEE International Conference on
E-Commerce Technology.
Sardinha, J. A. R. P., Milidi
´
u, R. L., Paranhos, P. M., Cunha,
P. M., and de Lucena, C. J. P. (2005). An Agent Based
Architecture for Highly Competitive Electronic Mar-
kets. In Russell, I. and Markov, Z., editors, FLAIRS
Conference, pages 326–332. AAAI Press.
Wong, W. Y., Zhang, D. M., and Kara-Ali, M. (2000). Ne-
gotiating With Experience. In CSIRO Mathematical
and Information Sciences.
Zeng, D. and Sycara, K. (1997). Benefits of Learning in Ne-
gotiation. In Proceedings of the 14th National Confer-
ence on Artificial Intelligence and 9th Innovative Ap-
plications of Artificial Intelligence Conference (AAAI-
97/IAAI-97), pages 36–42, Menlo Park. AAAI Press.
Zhang, S., Ye, S., Makedon, F., and Ford, J. (2004). A
Hybrid Negotiation Strategy Mechanism in an Auto-
mated Negotiation System. In Breese, J. S., Feigen-
baum, J., and Seltzer, M. I., editors, EC ’04: Proceed-
ings of the 5th ACM conference on Electronic com-
merce, pages 256–257, New York, NY, USA. ACM
Press.
ICEIS 2006 - SOFTWARE AGENTS AND INTERNET COMPUTING
158