Agent-based computational economics
Contents
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.
Computational World models
In order for agents to operate in computational worlds, methods and protocols are required. These methods and protocols enable interactions between agents, between agents and the world or artificial institutions e.g. market.[2]
Other 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
- ↑ 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
- ↑ TESFATSION, Leigh. Modeling Economies as Complex Adaptive Systems. Agent-Based Computational Economics: Modeling Economies as Complex Adaptive Systems [online]. 2010-03-24, 2010-03-24 [cit. 2012-06-18]. Dostupné z: http://www2.econ.iastate.edu/classes/econ308/tesfatsion/ACETutorial.pdf
