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The paper deals with behaviour of trading agents with the lowest level of bounded rationality on an electronic market where the double auction is applied as a trading mechanism. Two types of double auction have been considered: the clearing house and the continuous double auction. The agent behaviour is modelled using business strategies based on adaptive learning algorithms and imitation which is governed by replicator dynamics from evolutionary game theory. A case study describing optical bandwidth trading on the double auction electronic market is analyzed.