Agents, Equations and All That: On the Role of Agents in Understanding Complex Systems

  • Roberto Serra
  • Marco Villani
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4155)


Differential equations and agent-based models are different formalisms which can be applied to describe the evolution of complex systems. In this paper, it is shown how differential equations can describe interactions among agents: it is pointed out that their capabilities are broader than is often assumed, and it is argued that such an approach should be preferred whenever applicable. Also discussed are the circumstances in which it is necessary to resort to agent-based models, and a rigorous approach is advocated in these cases. In particular, the relationship between the model and a theory of the processes under consideration provides both stimuli and constraints for the model. This relationship is discussed both in general terms and with reference to a specific example, which concerns a model of innovation processes.


Cellular Automaton Innovation Process Information Processing Capability Zero Intelligence Evolve Complex System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Roberto Serra
    • 1
  • Marco Villani
    • 1
  1. 1.Dipartimento di Scienze Sociali, Cognitive e QuantitativeUniversità di Modena e Reggio EmiliaReggio Emilia

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