Time Series Analysis: Forecasting and Control
Time Series Analysis: Forecasting and Control
Inductive Learning Algorithms for Complex Systems Modeling
Inductive Learning Algorithms for Complex Systems Modeling
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
Concurrent Multiple-Issue Negotiation for Internet-Based Services
IEEE Internet Computing
Predicting opponent's moves in electronic negotiations using neural networks
Expert Systems with Applications: An International Journal
Empirical game-theoretic analysis of the TAC Supply Chain game
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Logic-based automated multi-issue bilateral negotiation in peer-to-peer e-marketplaces
Autonomous Agents and Multi-Agent Systems
Knowledge discovery for adaptive negotiation agents in e-marketplaces
Decision Support Systems
An efficient multilateral negotiation system for pervasive computing environments
Engineering Applications of Artificial Intelligence
Genius: negotiation environment for heterogeneous agents
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Agent-based negotiation and decision making for dynamic supply chain formation
Engineering Applications of Artificial Intelligence
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
A multi-agent system for distributed multi-project scheduling: An auction-based negotiation approach
Engineering Applications of Artificial Intelligence
A novel strategy for efficient negotiation in complex environments
MATES'12 Proceedings of the 10th German conference on Multiagent System Technologies
ABiNeS: An Adaptive Bilateral Negotiating Strategy over Multiple Items
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 02
Optimizing complex automated negotiation using sparse pseudo-input gaussian processes
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
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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 with unknown opponents under real-time constraints. In this paper we present a negotiation strategy called EMAR for this kind of environment that relies on a combination of Empirical Mode Decomposition (EM@?D) and Autoregressive Moving Average (AR@?MA). EMAR enables a negotiating agent to acquire an opponent model and to use this model for adjusting its target utility in real-time on the basis of an adaptive concession-making mechanism. Experimental results show that EMAR outperforms best performing agents from the recent Automated Negotiating Agents Competitions (ANAC) in a wide range of application domains. Moreover, an analysis based on empirical game theory is provided that shows the robustness of EMAR in different negotiation contexts.