Chaoticity analysis and control of pricing time series in multi-agent artificial demand-supply markets modeled by the genetic programming

Summary form only given. This paper deals with the chaoticity analysis of time series of input pricing on the demand/supply market generated by multi-agent systems and its applications to the control of chaotic behavior of input pricing. The agents´ learning processes are modeled by the coevolutionary genetic programming (GP). Five types of agents are introduced and within them a number of agents are assumed to be heterogeneous and to have their own rule for predicting the future pricing. Also we assume agents with random behavior.