Agent-based computational economics

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Resarch

Main pillars of ACE resarch[1]:

  • Empirical
  • Normative
  • Qualitativ insight and theory generation
  • Methodological advancement

Empirical

This area area stands for explaining possible reasons for observed regularities.


Computing methods

  • Linear Equations and Iterative Methods (Currently empty)
  • Optimization
  • Nonlinear Equations
  • Approximation
  • Numerical Integration and Differentiation
  • Monte Carlo and Simulation Methods (Currently empty)
  • Quasi-Monte Carlo Methods (Currently empty)
  • Finite Difference Methods (Currently empty)
  • Projection Methods for Functional Equations (Currently empty)
  • Numerical Dynamic Programming (Currently empty)
  • Regular Perturbations of Simple Systems (Currently empty)
  • Regular Perturbations in Multidimensional Systems (Currently empty)
  • Advanced Asymptotic Methods (Currently empty)
  • Solution Methods for Perfect Foresight Models (Currently empty)
  • Solving Rational Expectations Models

References

  1. ↑ TESFATSION, Leigh. Agent-Based Computational Economics: Growing Economies from the Bottom Up. IOWA STATE UNIVERSITY. Agent-Based Computational Economics [online]. 2012-05-02, 2012-05-02 [cit. 2012-06-18]. Dostupné z: http://www2.econ.iastate.edu/tesfatsi/ace.htm
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