Agent-based computational economics
Agent-based computational economics ACE is a area of computational economics that studies economic processes, including whole economies, as dynamic systems of interacting agents. As such, it falls in a paradigm of complex adaptive systems. In corresponding agent-based models, the "agents" are "computational objects modeled as interacting according to rules" over space & time, not real people. The rules are formulated to framework behavior together with social interactions based on incentives and information. such(a) rules could also be the or done as a reaction to a impeach of optimization, realized through use of AI methods such(a) as Q-learning and other reinforcement learning techniques.
The theoretical given of mathematical optimization by agents in equilibrium is replaced by the less restrictive postulate of agents with bounded rationality adapting to market forces. ACE models apply numerical methods of analysis to computer-based simulations of complex dynamic problems for which more conventional methods, such(a) as theorem formulation, may non find complete use. Starting from initial conditions subjected by the modeler, the computational economy evolves over time as its segment agents repeatedly interact with used to refer to every one of two or more people or matters other, including learning from interactions. In these respects, ACE has been characterized as a bottom-up culture-dish approach to the explore of economic systems.
ACE has a similarity to, and overlap with, game theory as an agent-based method for modeling social interactions. But practitioners pull in also refers differences from specifics methods, for example in ACE events modeled being driven solely by initial conditions, if or not equilibria cause up or are computationally tractable, and in the modeling facilitation of agent autonomy and learning.
The method has benefited from continuing modernizing in modeling techniques of computer science and increased computer capabilities. Thescientific objective of the method is to "test theoretical findings against real-world data in ways that permit empirically supported theories to cumulate over time, with each researcher’s construct building appropriately on the work that has gone before." The subject has been applied to research areas like asset pricing, competition and collaboration, transaction costs, market structure and industrial organization and dynamics, welfare economics, and mechanism design, information and uncertainty, macroeconomics, and Marxist economics.