Elements in Complexity and Agent-based Economics – serie

This Element works as non-technical overview of Agent-Based Modelling (ABM), a methodology which can be applied to economics, as well as fields of natural and social sciences. This Element presents the introductory notions and historical background of ABM, as well as a general overview of the tools and characteristics of this kind of models, with particular focus on more advanced topics like validation and sensitivity analysis. Agent-based simulations are an increasingly popular methodology which fits well with the purpose of studying problems of computational complexity in systems populated by heterogeneous interacting agents.

This Element works as non-technical overview of Agent-Based Modelling (ABM), a methodology which can be applied to economics, as well as fields of natural and social sciences. This Element presents the introductory notions and historical background of ABM, as well as a general overview of the tools and characteristics of this kind of models, with particular focus on more advanced topics like validation and sensitivity analysis. Agent-based simulations are an increasingly popular methodology which fits well with the purpose of studying problems of computational complexity in systems populated by heterogeneous interacting agents.

Neoclassical economics is heavily based on a formalistic method, primarily centred on mathematical deduction. Consequently, mainstream economists became overfocused on describing the states of an economy rather than understanding the processes driving these states. However, many phenomena arise from the intricate interactions among diverse elements, eluding explanation solely through micro-level rules. Such systems, characterised by emergent properties arising from interactions, are defined as complex. This Element delves into the complexity approach, portraying the economy as an evolving system undergoing structural changes over time.

Neoclassical economics is heavily based on a formalistic method, primarily centred on mathematical deduction. Consequently, mainstream economists became overfocused on describing the states of an economy rather than understanding the processes driving these states. However, many phenomena arise from the intricate interactions among diverse elements, eluding explanation solely through micro-level rules. Such systems, characterised by emergent properties arising from interactions, are defined as complex. This Element delves into the complexity approach, portraying the economy as an evolving system undergoing structural changes over time.

The aim of this Element is to understand how far mathematical theories based on active particles methods have been applied to describe the dynamics of complex systems in economics, and to look forward to further research perspectives in the interaction between mathematics and economics. The mathematical theory of active particles and the theory of behavioral swarms are selected for the above interaction. The mathematical approach considered in this work takes into account the complexity of living systems, which is a key feature of behavioral economics. The modeling and simulation of the dynamics of prices within a heterogeneous population is reviewed to show how mathematical tools can be used in real applications.