Dynamic bargaining with transaction costs
Management Science
Negotiation analysis: a characterization and review
Management Science
Rules of encounter: designing conventions for automated negotiation among computers
Rules of encounter: designing conventions for automated negotiation among computers
Negotiation and cooperation in multi-agent environments
Artificial Intelligence - Special issue on economic principles of multi-agent systems
Bayesian learning in negotiation
International Journal of Human-Computer Studies - Evolution and learning in multiagent systems
Beliefs, time and incomplete information in multiple encounter negotiations among autonomous agents
Annals of Mathematics and Artificial Intelligence
Dynamic Pricing on the Internet: Theory and Simulations
Electronic Commerce Research
Determining Successful Negotiation Strategies: An Evolutionary Approach
ICMAS '98 Proceedings of the 3rd International Conference on Multi Agent Systems
Dynamic Programming
Game theoretic and decision theoretic agents
The Knowledge Engineering Review
Agent-mediated electronic commerce: a survey
The Knowledge Engineering Review
Effect of bargaining in electronic commerce
International Journal of Electronic Commerce - Special issue: Intelligent agents for electronic commerce
ACM Transactions on Internet Technology (TOIT)
Auction advisor: an agent-based online-auction decision support system
Decision Support Systems
Learning bidding strategies with autonomous agents in environments with unstable equilibrium
Decision Support Systems
Mining Trading Partners' Preferences for Efficient Multi-Issue Bargaining in E-Business
Journal of Management Information Systems
Auction Advisor: an agent-based online-auction decision support system
Decision Support Systems
Applying hybrid case-based reasoning in agent-based negotiations for supply chain management
Expert Systems with Applications: An International Journal
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In this paper, we analyze an Internet agent-based market where non-cooperative agents using behavioral rules negotiate the price of a given product in a bilateral and sequential manner. In this setting, we study the optimal decision-making process of a buying agent that enters the market. Our approach is based on iNegotiation Analysis (Raiffa, 1982; Sebenuis, 1992) and we consider that the optimizing buying agent maximizes her discounted expected utility using subjective probabilities. The optimal decision-making process of the buying agent is treated as a stochastic control problem that can be solved by dynamic programming. Three types of behavioral agents are studied, namely conceder agents, boulware agents and imitative agents. A set of simulations is undertaken in order to predict the average outcome in a negotiation process for different parameters of the optimizing buying agent and for the three possible selling agents' behaviors. Finally, we compare the performance of the optimizing agent with that of behavioral buying agents.