Agents that reduce work and information overload
Communications of the ACM
A scalable comparison-shopping agent for the World-Wide Web
AGENTS '97 Proceedings of the first international conference on Autonomous agents
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Management Science - Special issue: Frontier research on information systems and economics
Communications of the ACM
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Computer Networks: The International Journal of Computer and Telecommunications Networking - electronic commerce
Autonomous Agents and Multi-Agent Systems
A personalized and integrative comparison-shopping engine and its applications
Decision Support Systems - Special issue: Agents and e-commerce business models
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IEEE Transactions on Knowledge and Data Engineering
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Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
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The Knowledge Engineering Review
Management Science
Designing personalized user experiences in eCommerce
Designing personalized user experiences in eCommerce
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Management Science
Shopbots: A Syntactic Present, A Semantic Future
IEEE Internet Computing
Scaling-up shopbots: a dynamic allocation-based approach
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Firefly-Inspired Synchronization for Improved Dynamic Pricing in Online Markets
SASO '08 Proceedings of the 2008 Second IEEE International Conference on Self-Adaptive and Self-Organizing Systems
Collaborative multi agent physical search with Probabilistic knowledge
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Journal of Theoretical and Applied Electronic Commerce Research
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Autonomous Agents and Multi-Agent Systems
Computer
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This article considers markets mediated by autonomous self-interested comparison-shopping agents. As in today’s markets, the agents do not charge buyers for their services but rather benefit from payments obtained from sellers upon the execution of a transaction. The agents aim at maximizing their expected benefit, taking into consideration the cost incurred by the search and competition dynamics that arise in the multi-agent setting. This article provides a comprehensive analysis of such models, based on search theory principles. The analysis results in a characterization of the buyers’ and agents’ search strategies in equilibrium. The main result of this article is that the use of self-interested comparison-shopping agents can result in a beneficial equilibrium, where both buyers and sellers benefit, in comparison to the case where buyers control the comparison-shopping agent, and the comparison-shopping agents necessarily do not lose. This, despite the fact that the service is offered for free to buyers and its cost is essentially covered by sellers. The analysis generalizes to any setting where buyers can use self-interested agents capable of effectively performing the search (e.g., evaluating opportunities) on their behalf.