Hidden order: how adaptation builds complexity
Hidden order: how adaptation builds complexity
Computational and mathematical organization theory: perspective and directions
Computational & Mathematical Organization Theory
WSC '04 Proceedings of the 36th conference on Winter simulation
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Evolutionary Computation
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The purpose of this paper is to demonstrate the usefulness of complex systems paradigm in studying real life phenomena. In this paper, we depict the phenomena from two distinctive domains: the competitive behavior of power generators in an auction-based electricity market and group dynamics and performance in an organizational context. Agent based modeling has been employed as the research method to conduct computer experiments. In this paper, we include the formal knowledge representation defining the types of agents in each domain, together with the properties, relationships, processes and events associated with the agents. Emergence from the first study include collusion and capacity withholding to inflate price, whereas in the second study, we observe that timely completion of group task is not always accompanied by a high level of group satisfaction. These emergence are evidence that we can gain new knowledge from the Sciences of the Artificial.