Agent-Based Computational Economics: Growing Economies From the Bottom Up

By Leigh Tesfatsion. Artificial Life, 2002

1,011 citations recorded by the source corpus.

Agent-based computational economics (ACE) is the computational study of economies modeled as evolving systems of autonomous interacting agents. Thus, ACE is a specialization of economics of the basic complex adaptive systems paradigm. This study outlines the main objectives and defining characteristics of the ACE methodology and discusses similarities and distinctions between ACE and artificial life research. Eight ACE research areas are identified, and a number of publications in each area are highlighted for concrete illustration. Open questions and directions for future ACE research are also considered. The study concludes with a discussion of the potential benefits associated with ACE modeling, as well as some potential difficulties.

Subfields: Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/cf4317406dd12400daa942bbfefae67e004f50a1

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In Economics and Econometrics

Citations in the corpus

Self-Organisation: Paradigms and Applications (2003, neutral): “This behaviour has been studied in robotics through simulations [29] and real implementations [30].”
The Emergence of Service Science: Toward Systematic Service Innovations to Accelerate Co‐Creation of Value (2008, methodology): “Agent-based modeling techniques first developed for artificial intelligence are now being applied in new areas, such as computational organization theory (Carley 2002) and agent-based computational economics (Tesfatsion 2002).”
Tutorial on Agent-Based Modeling and Simulation PART 2: How to Model with Agents (2006, background): “The field of Agent-based Computational Economics (ACE) has grown up around the application of ABMS to economic systems (Tesfatsion 2002, 2005).”
Tutorial on agent-based modeling and simulation (2005, background): “The field of Agent-based Computational Economics (ACE) has grown up around the application of ABMS to economic systems (Tesfatsion 2002, 2005).”
Empirical Validation of Agent-Based Models: Alternatives and Prospects (2007, background): “The properties of macro-dynamics can only be properly understood as the outcome of micro-dynamics involving basic entities/ agents (cf. Tesfatsion 2002).”
A CyberGIS Framework for the Synthesis of Cyberinfrastructure, GIS, and Spatial Analysis (2010, methodology): “These methods, often combined to provide problem-solving and decision-making support (Newell and Simon 1972; Holland et al. 1986; Pagels 1988), have been extensively applied in many domains (Tesfatsion 2002; Miller and Wentz 2003; Goodchild and Janelle 2004).”
Emergent Macroeconomics: An Agent-Based Approach to Business Fluctuations (2008, neutral): “2Tesfatsion and Judd (2006) provides a comprehensive survey of the different viewpoints from which the exploration of behaviour of individual agents can be carried out.”
A standard protocol for describing individual-based and agent-based models (2006, methodology): “…" gap models " (Liu and Ashton, 1995); the fish cohort model of DeAngelis et al. (1980), which initiated large research projects using IBMs (Tyler and Rose, 1994; Van Winkle et al., 1993); and the fish school model of Huth and Wissel (1992, 1994), which was independently re-implemented and…”
Agent-based computational economics: modeling economies as complex adaptive systems (2003, background): “This paper is an abbreviated version of [20].”