Overview on agent-based social modelling and the use of formal languages

Transdisciplinary Models and Applications investigates a variety of programming languages used in validating and verifying models in order to assist in their eventual implementation. This book will explore different methods of evaluating and formalizing simulation models, enabling computer and industrial engineers, mathematicians, and students working with computer simulations to thoroughly understand the progression from simulation to product, improving the overall effectiveness of modeling systems.Postprint (author's final draft

OperA/ALIVE/OperettA

Comprehensive models for organizations must, on the one hand, be able to specify global goals and requirements but, on the other hand, cannot assume that particular actors will always act according to the needs and expectations of the system design. Concepts as organizational rules (Zambonelli 2002), norms and institutions (Dignum and Dignum 2001; Esteva et al. 2002), and social structures (Parunak and Odell 2002) arise from the idea that the effective engineering of organizations needs high-level, actor-independent concepts and abstractions that explicitly define the organization in which agents live (Zambonelli 2002).Peer ReviewedPostprint (author's final draft

Weaving a fabric of socially aware agents

The expansion of web-enabled social interaction has shed light on social aspects of intelligence that have not been typically studied within the AI paradigm so far. In this context, our aim is to understand what constitutes intelligent social behaviour and to build computational systems that support it. We argue that social intelligence involves socially aware, autonomous individuals that agree on how to accomplish a common endeavour, and then enact such agreements. In particular, we provide a framework with the essential elements for such agreements to be achieved and executed by individuals that meet in an open environment. Such framework sets the foundations to build a computational infrastructure that enables socially aware autonomy.This work has been supported by the projects EVE(TIN2009-14702-C02-01) and AT (CSD2007-0022)Peer Reviewe

The Logic of the Method of Agent-Based Simulation in the Social Sciences: Empirical and Intentional Adequacy of Computer Programs

The classical theory of computation does not represent an adequate model of reality for simulation in the social sciences. The aim of this paper is to construct a methodological perspective that is able to conciliate the formal and empirical logic of program verification in computer science, with the interpretative and multiparadigmatic logic of the social sciences. We attempt to evaluate whether social simulation implies an additional perspective about the way one can understand the concepts of program and computation. We demonstrate that the logic of social simulation implies at least two distinct types of program verifications that reflect an epistemological distinction in the kind of knowledge one can have about programs. Computer programs seem to possess a causal capability (Fetzer, 1999) and an intentional capability that scientific theories seem not to possess. This distinction is associated with two types of program verification, which we call empirical and intentional verification. We demonstrate, by this means, that computational phenomena are also intentional phenomena, and that such is particularly manifest in agent-based social simulation. Ascertaining the credibility of results in social simulation requires a focus on the identification of a new category of knowledge we can have about computer programs. This knowledge should be considered an outcome of an experimental exercise, albeit not empirical, acquired within a context of limited consensus. The perspective of intentional computation seems to be the only one possible to reflect the multiparadigmatic character of social science in terms of agent-based computational social science. We contribute, additionally, to the clarification of several questions that are found in the methodological perspectives of the discipline, such as the computational nature, the logic of program scalability, and the multiparadigmatic character of agent-based simulation in the social sciences.Computer and Social Sciences, Agent-Based Simulation, Intentional Computation, Program Verification, Intentional Verification, Scientific Knowledge

Endogenous Needs, Values and Technology

Standard economic textbooks usually start with the assumptions that there exists • a set of representative consumers with exogenously given, fixed preference structures, • a set of representative production units with exogenously given, fixed production functions, • a set of identical market mechanisms determining a vector of endogenous prices enabling coordination of optimisation of the former two types of representative agents. Economic history shows that the last two hundred years of evolution in most advanced was mainly characterized by • an incredible change of dimensions and quantities of goods and services keeping preference structures in permanent flux, • an enormous amount of entry, exit and modification of production units and their corresponding production processes, • market mechanisms are constantly diversifying; the actual, observed price vector being the result of a multitude of market institutions that represent locally and temporarily frozen political and economic forces. Standard economic textbooks thus are simply inadequate to deal with economic facts, critique from science and practice righteously is booming. The following arguments will sketch a modelling framework that turns these inadequate methodological assumptions upside down: Needs that motivate consumers are explained endogenously. The growth of the heterogeneous set of households is made explicit. Evolution of technology is endogenously determined namely as strategic necessity of a changing structure of production units. Finally the forms of social organisation are assumed to be modelled explicitly, or, more precisely, the framework enabling the model-builder to formulate a specific, temporarily valid set of fixations regulating interactions in a society is characterized. While this last module concerns the more or less institutionalised outcome of struggling and bargaining of the involved agents – thus is meant to render at least some temporary stability by being itself stable – the other two modules (needs and technology) are far more volatile. Of course, in the long-run they all are interdependent. It follows that from a logical point of view the forms of social organization - i.e. the temporary stable arrangements of a given society for a given historical era – are the starting point to be developed first.needs; value; technology; evolutionary economics

Alternative Approaches to the Empirical Validation of Agent-Based Models

This paper draws on the metaphor of a spectrum of models ranging from the most theory-driven to the most evidence-driven. The issue of concern is the practice and criteria that will be appro- priate to validation of different models. In order to address this concern, two modelling approaches are investigated in some detailed – one from each end of our metaphorical spectrum. Windrum et al. (2007) (http://jasss.soc.surrey.ac.uk/10/2/8.html) claimed strong similarities between agent based social simulation and conventional social science – specifically econometric – approaches to empirical modelling and on that basis considered how econometric validation techniques might be used in empirical social simulations more broadly. An alternative is the approach of the French school of \'companion modelling\' associated with Bousquet, Barreteau, Le Page and others which engages stakeholders in the modelling and validation process. The conventional approach is con- strained by prior theory and the French school approach by evidence. In this sense they are at opposite ends of the theory-evidence spectrum. The problems for validation identified by Windrum et al. are shown to be irrelevant to companion modelling which readily incorporate complexity due to realistically descriptive specifications of individual behaviour and social interaction. The result combines the precision of formal approaches with the richness of narrative scenarios. Companion modelling is therefore found to be practicable and to achieve what is claimed for it and this alone is a key difference from conventional social science including agent based computational economics.Social Simulation, Validation, Companion Modelling, Data Generating Mechanisms, Complexity

Constraint rule-based programming of norms for electronic institutions

Peer reviewedPostprin

On the convergence of autonomous agent communities

This is the post-print version of the final published paper that is available from the link below. Copyright @ 2010 IOS Press and the authors.Community is a common phenomenon in natural ecosystems, human societies as well as artificial multi-agent systems such as those in web and Internet based applications. In many self-organizing systems, communities are formed evolutionarily in a decentralized way through agents' autonomous behavior. This paper systematically investigates the properties of a variety of the self-organizing agent community systems by a formal qualitative approach and a quantitative experimental approach. The qualitative formal study by applying formal specification in SLABS and Scenario Calculus has proven that mature and optimal communities always form and become stable when agents behave based on the collective knowledge of the communities, whereas community formation does not always reach maturity and optimality if agents behave solely based on individual knowledge, and the communities are not always stable even if such a formation is achieved. The quantitative experimental study by simulation has shown that the convergence time of agent communities depends on several parameters of the system in certain complicated patterns, including the number of agents, the number of community organizers, the number of knowledge categories, and the size of the knowledge in each category