High-performance bidding agents for the continuous double auction
Proceedings of the 3rd ACM conference on Electronic Commerce
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
On Agent-Mediated Electronic Commerce
IEEE Transactions on Knowledge and Data Engineering
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
Strategic bidding in continuous double auctions
Artificial Intelligence
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
Metastrategies in the Colored Trails game
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Scaling simulation-based game analysis through deviation-preserving reduction
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
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In this paper, we investigate the effectiveness of different types of bidding behaviour for trading agents in the Continuous Double Auction (CDA). Specifically, we consider behavioural types that are neutral (expected profit maximising), passive (targeting a higher profit than neutral) and aggressive (trading off profit for a better chance of transacting). For these types, we employ an evolutionary game-theoretic analysis to determine the population dynamics of agents that use them in different types of environments, including dynamic ones with market shocks. From this analysis, we find that given a symmetric demand and supply, agents are most likely to adopt neutral behaviour in static environments, while there tends to be more passive than neutral agents in dynamic ones. Furthermore, when we have asymmetric demand and supply, agents invariably adopt passive behaviour in both static and dynamic environments, though the gain in so doing is considerably smaller than in the symmetric case.