Explorations in evolutionary robotics
Adaptive Behavior
Adaptive agents in a persistent shout double auction
Proceedings of the first international conference on Information and computation economies
Strategic sequential bidding in auctions using dynamic programming
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 2
Applying evolutionary game theory to auction mechanism design
Proceedings of the 4th ACM conference on Electronic commerce
A Fuzzy-Logic Based Bidding Strategy for Autonomous Agents in Continuous Double Auctions
IEEE Transactions on Knowledge and Data Engineering
Speculation Agents for Dynamic Multi-Period Continuous Double Auctions in B2B Exchanges
HICSS '04 Proceedings of the Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS'04) - Track 7 - Volume 7
Rule-Based Specification of Auction Mechanisms
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 2
Developing adaptive auction mechanisms
ACM SIGecom Exchanges
Autonomous Adaptive Agents for Single Seller Sealed Bid Auctions
Autonomous Agents and Multi-Agent Systems
Competitive coevolution through evolutionary complexification
Journal of Artificial Intelligence Research
Use of Markov chains to design an agent bidding strategy for continuous double auctions
Journal of Artificial Intelligence Research
Agent-human interactions in the continuous double auction
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Exploring bidding strategies for market-based scheduling
Decision Support Systems - Special issue: The fourth ACM conference on electronic commerce
An evolutionary game-theoretic comparison of two double-auction market designs
AAMAS'04 Proceedings of the 6th AAMAS international conference on Agent-Mediated Electronic Commerce: theories for and Engineering of Distributed Mechanisms and Systems
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The "ZIP" adaptive trading algorithm has been demonstrated to outperform human traders in experimental studies of continuous double auction (CDA) markets. The original ZIP algorithm requires the values of eight control parameters to be set correctly. A new extension of the ZIP algorithm, called ZIP60, requires the values of 60 parameters to be set correctly. ZIP60 is shown here to produce significantly better results than the original ZIP (called "ZIP8" hereafter), for negligable additional computational costs. A genetic algorithm (GA) is used to search the 60-dimensional ZIP60 parameter space, and it finds parameter vectors that yield ZIP60 traders with mean scores significantly better than those of ZIP8s. This paper shows that the optimizing evolutionary search works best when the GA itself controls the dimensionality of the search-space, so that the search commences in an 8-d space and thereafter the dimensionality of the search-space is gradually increased by the GA until it is exploring a 60-d space. Furthermore, the results from ZIP60 cast some doubt on prior ZIP8 results concerning the evolution of new 'hybrid' auction mechanisms that appeared to be better than the CDA.