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This paper is about the theoretical implications of agent-based modeling exercises. Construction of an agent-based model challenges a social scientist to formalize many concepts and relationships that would have remained implicit or unrecognized. While formalizing these "unimportant" assumptions can be a nuisance, it can also have substantial theoretical payoffs. In order to fill the gaps of the model, the researcher is forced to confront the gaps in the theory that motivated the model in the first place. Using examples drawn from several large political science simulation models, the paper argues that frailty, defined as unpredictability in the behavior of agents, is often required in order to bring closure to the modeling exercise. It is difficult (or impossible) to square the dynamic or aggregate implications of the agent-based model with observations without placing a substantial amount of emphasis on frailty. Hence, the component in behavior that we often treat as "error" in empirical analysis is actually a vital part of the glue that makes the many different moving parts of a social system interact in coherent ways. The example models were developed with the Swarm simulation system (http://www.swarm.org) during the last decade.

This is the publisher's version, also available electronically from https://sites.google.com/a/fspub.unibuc.ro/european-quarterly-of-political-attitudes-and-mentalities/Home ; This paper is about the theoretical implications of agent-based modeling exercises. Construction of an agent-based model challenges a social scientist to formalize many concepts and relationships that would have remained implicit or unrecognized. While formalizing these "unimportant" assumptions can be a nuisance, it can also have substantial theoretical payoffs. In order to fill the gaps of the model, the researcher is forced to confront the gaps in the theory that motivated the model in the first place. Using examples drawn from several large political science simulation models, the paper argues that frailty, defined as unpredictability in the behavior of agents, is often required in order to bring closure to the modeling exercise. It is difficult (or impossible) to square the dynamic or aggregate implications of the agent-based model with observations without placing a substantial amount of emphasis on frailty. Hence, the component in behavior that we often treat as "error" in empirical analysis is actually a vital part of the glue that makes the many different moving parts of a social system interact in coherent ways. The example models were developed with the Swarm simulation system (http://www.swarm.org) during the last decade.

Edited by André Grow and Jan Van BavelSpringer International Publishing 2017 ISBN: 978-3-319-32281-0Hardcover, $159.99 US, eBook, $119 US, 513 pp.

Basel III is a recently-agreed regulatory standard for bank capital adequacy with focus on the macroprudential dimension of banking regulation, i.e., the system- wide implications of banks' lending and risk. An important Basel III provision is to reduce procyclicality of present banking regulation and promote countercyclical capital buffers for banks. The Eurace agent-based macroeconomic model and sim- ulator has been recently showed to be able to reproduce a credit-fueled boom-bust dynamics where excessive bank leverages, while benefitting in the short term, have destabilizing effects in the medium-long term. In this paper we employ the Eu- race model to test regulatory policies providing time varying capital requirements for banks, based on mechanisms that enforce banks to build up or release capital buffers, according to the overall conditions of the economy. As conditioning variables for these dynamic policies, both the unemployment rate and the aggregate credit growth have been considered. Results show that the dynamic regulation of capital requirements is generally more successful than fixed tight capital requirements in stabilizing the economy and improving the macroeconomic performance.

An organization is a collection of agents that interact and produce some form of output. Formal organizations - such as corporations and governments - are typically constructed for an explicit purpose though this purpose needn't be shared by all organizational members. An entrepreneur who creates a firm may do so in order to generate personal wealth but the worker she hires may have very different goals. As opposed to more amorphous collections of agents such as friendship networks and societies at large, organizations have a formal structure to them (though informal structures typically emerge as well) with the prototypical example being a corporation's organizational chart. This structure serves to define lines of communication and the distribution of decision-making. Organizations are also distinguished by their well-defined boundaries as reflected in a clear delineation as to who is and who is not a member. This boundary serves to make organizations a natural unit of selection; for example, corporations are formed and liquidated though they can also morph into something different through activities like mergers.