Evolutionary Computation
Evolving cooperative bidding strategies in a power market
Applied Intelligence
Simulation of a Peer to Peer Market for Grid Computing
ASMTA '08 Proceedings of the 15th international conference on Analytical and Stochastic Modeling Techniques and Applications
Dynamic Polymorphic Agents Scheduling and Execution Using Artificial Immune Systems
ICARIS '08 Proceedings of the 7th international conference on Artificial Immune Systems
A learning classifier system for mazes with aliasing clones
Natural Computing: an international journal
An Agent-Based Simulation Model for Analysis on Marketing Strategy Considering Promotion Activities
KES-AMSTA '09 Proceedings of the Third KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications
A More Realistic Peer-to-Peer Grid Market Model
EPEW '09 Proceedings of the 6th European Performance Engineering Workshop on Computer Performance Engineering
Agent-based simulation of electricity markets: a survey of tools
Artificial Intelligence Review
Modeling multi-agent labor market based on co-evolutionary computation and game theory
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
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The deregulation of electricity markets has continued apace around the globe. The best structure for deregulated markets is a subject of much debate, and the consequences of poor structural choices can be dramatic. Understanding the effect of structure on behavior is essential, but the traditional economics approaches of field studies and experimental studies are particularly hard to conduct in relation to electricity markets. This paper describes an agent based computational economics approach for studying the effect of alternative structures and mechanisms on behavior in electricity markets. Autonomous adaptive agents, using hierarchical learning classifier systems, learn through competition in a simulated model of the UK market in electricity generation. The complex agent structure was developed through a sequence of experimentation to test whether it was capable of meeting the following requirements: first, that the agents are able to learn optimal strategies when competing against nonadaptive agents; second, that the agents are able to learn strategies observable in the real world when competing against other adaptive agents; and third, that cooperation without explicit communication can evolve in certain market situations. The potential benefit of an evolutionary economics approach to market modeling is demonstrated by examining the effects of alternative payment mechanisms on the behavior of agents.