Multiagent systems: a modern approach to distributed artificial intelligence
Multiagent systems: a modern approach to distributed artificial intelligence
E-business: roadmap for success
E-business: roadmap for success
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Doing Business in the Wired World
Computer
Agent-Oriented Concepts to Foster the Automation of e-Business
DEXA '00 Proceedings of the 11th International Workshop on Database and Expert Systems Applications
The IDEAL Approach to Internet-Based Negotiation for E-Business
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Reinforcement learning: a survey
Journal of Artificial Intelligence Research
Dynamic evaluation approach for virtual conflict decision training
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Multi-agent system approach to context-aware coordinated web services under general market mechanism
Decision Support Systems
Building a Multiple-Criteria Negotiation Support System
IEEE Transactions on Knowledge and Data Engineering
Multi-agent system approach to context-aware coordinated web services under general market mechanism
Decision Support Systems
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Decision-making within electronic business processes is frequently swamped by conflictive situations. Dynamism in real-life negotiation poses challenges when creating models of how business people interact and settle down strategic differences. Dispute resolutions are not fully addressed by current e-business decision-support systems (DSS). To attack this problem, we resort to an analogous model: soccer match strategies. These games are dynamic thrive with conflicts. Both worlds are mapped using a model in which agents cooperate toward common goals. As a result, we show a functional analogy between collaborative strategies in a soccer match and business-to-business processes. We present Java-based soccer and B2B simulators.