Time Series Analysis: Forecasting and Control
Time Series Analysis: Forecasting and Control
Predicting Agents Tactics in Automated Negotiation
IAT '04 Proceedings of the IEEE/WIC/ACM International Conference on Intelligent Agent Technology
Learning on opponent's preferences to make effective multi-issue negotiation trade-offs
ICEC '04 Proceedings of the 6th international conference on Electronic commerce
Modeling opponent decision in repeated one-shot negotiations
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Predicting partner's behaviour in agent negotiation
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Predicting opponent's moves in electronic negotiations using neural networks
Expert Systems with Applications: An International Journal
Genius: negotiation environment for heterogeneous agents
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Using Gaussian processes to optimise concession in complex negotiations against unknown opponents
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume One
An efficient automated negotiation strategy for complex environments
Engineering Applications of Artificial Intelligence
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A complex and challenging bilateral negotiation environment for rational autonomous agents is where agents negotiate multi-issue contracts in unknown application domains against unknown opponents under real-time constraints. In this paper we present a novel negotiation strategy called EMAR for this kind of environment which is based on a combination of Empirical Mode Decomposition (EMD) and Autoregressive Moving Average (ARMA). EMAR enables a negotiating agent to adjust its target utility and concession rate adaptively in real-time according to the behavior of its opponent. The experimental results show that this new strategy outperforms the best agents from the latest Automated Negotiation Agents (ANAC) Competition in a wide range of application domains.