Detecting Unsuccessful Automated Negotiation Threads When Opponents Employ Hybrid Strategies

Authors:
Ioannis Papaioannou;Ioanna Roussaki;Miltiades Anagnostou
Affiliations:
School of Electrical and Computer Engineering, National Technical University of Athens, Athens, Greece 157-73;School of Electrical and Computer Engineering, National Technical University of Athens, Athens, Greece 157-73;School of Electrical and Computer Engineering, National Technical University of Athens, Athens, Greece 157-73
Venue:
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence
Year:
2008

Citing 12
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Abstract

In artificial intelligence systems, building agents that negotiate on behalf of their owners aiming to maximise their utility is a quite challenging research field. In this paper, such agents are enhanced with techniques based on neural networks (NNs) to predict their opponents' hybrid negotiation behaviour, thus achieving more profitable results. The NNs are used to early detect the cases where agreements are not achievable, supporting the decision of the agents to withdraw or not from the negotiation threads. The designed NN-assisted negotiation strategies have been evaluated via extensive experiments and are proven to be very useful.