Designing neural networks using genetic algorithms
Proceedings of the third international conference on Genetic algorithms
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Multi-Agent Simulation of Virtual Consumer Populations in a Competitive Market
SCAI '01 Proceedings of the Seventh Scandinavian Conference on Artificial Intelligence
A Genetic Algorithm Discovers Particle-Based Computation in Cellular Automata
PPSN III Proceedings of the International Conference on Evolutionary Computation. The Third Conference on Parallel Problem Solving from Nature: Parallel Problem Solving from Nature
Modeling agents and interactions in agricultural economics
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Application of complex adaptive systems to pricing of reproducible information goods
Decision Support Systems
System implementation issues of dynamic discrete disaster decision simulation system (D4S2): phase I
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Small world network model of personal consumption: Demand-side management in an expert system
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
Multi-agent based simulation: where are the agents?
MABS'02 Proceedings of the 3rd international conference on Multi-agent-based simulation II
An agent-based diffusion model with consumer and brand agents
Decision Support Systems
An artificial maieutic approach for eliciting experts' knowledge in multi-agent simulations
MABS'05 Proceedings of the 6th international conference on Multi-Agent-Based Simulation
The impact of recommender systems on item-, user-, and rating-diversity
ADMI'11 Proceedings of the 7th international conference on Agents and Data Mining Interaction
Simulation of customers behaviour as a method for explaining certain market characteristic
Transactions on Computational Collective Intelligence IX
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Our goal is to create a virtual consumer population that can be used for simulating the effects of marketing strategies in a competing market context. That requires having a consumers' behavioral model allowing the representation of observed individual behaviors and the simulation of a large population of consumers. That also requires finding the parameters' values characterizing the virtual population that reproduces real market evolutions. This paper proposes a consumer behavioral model based on a set of behavioral primitives such as imitation, conditioning and innovativeness, which are founded on the new concept of behavioral attitude. It shows that this model provides an interpretation of the main concepts and cognitive features, issued from marketing research and psycho-sociology works on consumption. The paper presents also the CUstomer BEhavior Simulator (CUBES), which has been realized for implementing the customer model and leading multi-agents simulations. It shows how genetic algorithms (GA), in addition to multi-agent systems, are used to fit the characteristics of the virtual consumers' population into a global realistic market behavior.