Solution concepts in coevolutionary algorithms
Solution concepts in coevolutionary algorithms
Exploring bidding strategies for market-based scheduling
Decision Support Systems - Special issue: The fourth ACM conference on electronic commerce
A game-theoretic memory mechanism for coevolution
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
IEEE Transactions on Evolutionary Computation
A comparison of distributed and centralised agent based bundling systems
Proceedings of the ninth international conference on Electronic commerce
Empirical game-theoretic analysis of the TAC Supply Chain game
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Selecting strategies using empirical game models: an experimental analysis of meta-strategies
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2
Engineering large-scale distributed auctions
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3
Evolutionary dynamics for designing multi-period auctions
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3
Stronger CDA strategies through empirical game-theoretic analysis and reinforcement learning
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
What the 2007 TAC Market Design Game tells us about effective auction mechanisms
Autonomous Agents and Multi-Agent Systems
Evolutionary mechanism design: a review
Autonomous Agents and Multi-Agent Systems
Co-evolution of cooperative strategies under egoism
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Frequency adjusted multi-agent Q-learning
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Strategy exploration in empirical games
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
ALAMAS'05/ALAMAS'06/ALAMAS'07 Proceedings of the 5th , 6th and 7th European conference on Adaptive and learning agents and multi-agent systems: adaptation and multi-agent learning
Auctions, evolution, and multi-agent learning
ALAMAS'05/ALAMAS'06/ALAMAS'07 Proceedings of the 5th , 6th and 7th European conference on Adaptive and learning agents and multi-agent systems: adaptation and multi-agent learning
Metastrategies in the Colored Trails game
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
A grey-box approach to automated mechanism design
Electronic Commerce Research and Applications
Replicator dynamics for multi-agent learning: an orthogonal approach
ALA'09 Proceedings of the Second international conference on Adaptive and Learning Agents
Scaling simulation-based game analysis through deviation-preserving reduction
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
| Hi-index | 0.00 |
We present a novel method for automatically acquiring strategies for the double auction by combining evolutionary optimization together with a principled game-theoretic analysis. Previous studies in this domain have used standard co-evolutionary algorithms, often with the goal of searching for the "best" trading strategy. However, we argue that such algorithms are often ineffective for this type of game because they fail to embody an appropriate game-theoretic solution-concept, and it is unclear, what, if anything, they are optimizing. In this paper, we adopt a more appropriate criterion for success from evolutionary game-theory based on the likely adoption-rate of a given strategy in a large population of traders, and accordingly we are able to demonstrate that our evolved strategy performs well.