Content:
Grid Computing promises a flexible infrastructure for complex, dynamic and distributed resource sharing. Within this field, numerous economical questions have to be solved, for example the optimal allocation of resources to grid users while assuring some specific quality of service for all users. In order to approach complex economic problems, the use of analytical methods usually requires making numerous simplifying assumptions, for example the rational or homogeneous behavior of market participants. Moreover, these methods use high level models of the market which are too abstract to be profitably used as a basis of practical implementation. Recently, the technical availability of multiagent systems and multiagent simulations has nurtured a new field in economic research: Agent-based Computational Economics (ACE). Within this new research domain, computer based simulation models are applied to understand and analyze complex economic systems. Software agents act in an economic environment, e.g. are specified to exhibit strategic behavior for utility maximization. Especially in complex domains like Grid markets (e.g. for trading computational resources), approaches from the autonomous agents domain can serve very well in order to understand the way, the definition of market mechanisms affect the market outcome for the individual participants. Insofar, this interdisciplinary workshop addresses computer scientists (Grid computing, artificial intelligence, distributed systems, autonomic computing), economists (game theory, evolutionary economics, neo-institutional economics), cognitive science researchers (strategic behavior, automated negotiation) and practitioners.

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