The agent service brokering problem as a generalised travelling salesman problem
Proceedings of the third annual conference on Autonomous Agents
Building Large Knowledge-Based Systems; Representation and Inference in the Cyc Project
Building Large Knowledge-Based Systems; Representation and Inference in the Cyc Project
An algorithm for optimal winner determination in combinatorial auctions
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
Taming the computational complexity of combinatorial auctions: optimal and approximate approaches
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
Agents in E-commerce: state of the art
Knowledge and Information Systems
| Hi-index | 0.00 |
Deregulation of telecommunications has meant an increase in third-party service provision, personalized service delivery and integrated networks and media. The efficient allocation of services, without human intervention, to satisfy advanced service requirements spanning several networks is a crucial task. This can be modeled as a winner determination problem in combinatorial auctions where there are multiple services, service providers and winner determination criteria (like cost, bandwidth, delay, etc) but we have shown the problem is NP-complete. This paper describes a new two-stage algorithm for optimal anytime winner determination. In the first stage, a hierarchical task network planner is used to decompose a task into subtasks that can be solved by the available services. In the second stage, a genetic algorithm with heuristics is used to find the optimal combination of service providers to provide the services identified. We show through various experiments that the genetic algorithm finds optimal solutions quicker than a modified depth-first search algorithm.