=Paper=
{{Paper
|id=Vol-223/paper-42
|storemode=property
|title=Simulation as Formal and Generative Social Science: The Very Idea
|pdfUrl=https://ceur-ws.org/Vol-223/8.pdf
|volume=Vol-223
|authors=Nuno David (ISCTE),Jaime Sichman (University of São Paulo),Helder Coelho (University of Lisbon)
|dblpUrl=https://dblp.org/rec/conf/eumas/DavidSC06
}}
==Simulation as Formal and Generative Social Science: The Very Idea==
https://ceur-ws.org/Vol-223/8.pdf
A PHILOSOPHICAL PERSPECTIVE OF MULTIAGENT-BASED
SIMULATION IN THE SOCIAL SCIENCES
Nuno Davida Jaime Simão Sichmanb Helder Coelho c
a
Department of Information Science and Technology, ISCTE, Lisbon, Portugal
b
Intelligent Techniques Laboratory, University of São Paulo, São Paulo, Brazil
c
Department of Informatics, University of Lisbon, Lisbon, Portugal
Abstract
From the very beginning of the multiagent-systems paradigm, the sources of analogies between
agent-based technologies and models of actual social systems fomented interdisciplinary efforts between
computer and social scientists. Nowadays this trend reflects an intense interface of research across the
computer and social sciences, under the umbrella of a consolidated scientific field, which is called agent-
based social simulation. Several reasons prompt a philosophical analysis of this scientific domain,
relevant to both computer and social scientists that use multiagent systems. Conventional methodologies
of computer science and artificial intelligence model the mechanism of executing a program in a
computer like a process of formal inference. However, in [1, 2] the formal and empirical-generative
perspectives of computation are demonstrated to be inadequate to secure the goals of simulation in the
social sciences. Particular emphasis is given to agent-based simulation methods. Simulation does not
resemble formal demonstrations or generative mechanisms that deductively explain how certain agent-
based models are sufficient to generate emergent macrostructures of interest. The description of
scientific practice implies additional epistemic conceptions of scientific knowledge. Previous works
identified three kinds of knowledge that account for a comprehensive description of the discipline:
formal, empirical and intentional knowledge [3, 4]. This extended abstract summarizes claims we have
further presented in [1] and published in [2]: The use of formal conceptions of computation to describe
simulation is refuted, the roles of programming languages according to intentional accounts of
computation are identified, and the new role of iconographic programming languages and aesthetic
machines in simulation platforms are characterized.
1 Introduction
From the very beginning of the multiagent-systems paradigm, the sources of analogies between agent-
based technologies and models of actual social systems fomented interdisciplinary efforts between
computer and social scientists . Nowadays this trend reflects a new interface of research across the
computer and social sciences, under the umbrella of a consolidated scientific field, usually called
agent-based social simulation. Several reasons prompt a philosophical analysis of this scientific
domain, relevant to both computer and social scientists . In general, agent-based models and simulations
have been contributing to an inter- and multi-disciplinary scientific praxis , which contributes to
establishing new alternatives to traditional scientific methodologies. This should lead to the elaboration
of new philosophical perspectives about the rules of the game as they are currently played in
simulation.
The goal of our work presented and published in [1, 2, 3, 4] has been to characterize the actual
practice of computation for modelling social theory and phenomena with agent-based models ,
especially with reference to its epistemological basis and the particular kind of scientific knowledge
that this methodology is providing. In particular, in [3, 4] we demonstrated that the logic of social
simulation implies at least three distinct types of program verification in computer science, which
reflect an epistemological distinction in the kind of knowledge one can have about programs or
simulations. Whereas such knowledge may ultimately be characterized as merely interpretative the role
of complexity sciences suggests a further categorization beyond the traditional borders of formal and
empirical knowledge, reflecting three distinct contexts of scientific practice and knowledge: formal,
empirical and intentional knowledge.
Recently, a number of essays debated epistemological perspectives on social science simulation
(see [5]). Either by viewing simulation as a process of imitation, stylized facts, or intentional adequacy
between programs and theory, the tendency is to emphasize the interpretative character of social
science in simulation, notwithstanding its application as a useful methodology for approaching
complexity. Nevertheless, while the interpretative character of social science is being slowly
recognized into simulation, the formal character of computer science pervades the scientific culture of
simulation, as well as most of its methodological arguments. However, the formal perspective alone
does not seem to be compatible with simulation in the social sciences . Recent work, presented in [1]
and published in [2], demonstrated the classical account of computation to be inadequate to secure the
goals of simulation in the social sciences. Simulation does not resemble formal deductive
demonstrations or generative mechanisms that explain how certain agent-based models are sufficient to
generate emergent macrostructures of interest. The justification of results implies additional epistemic
conceptions of scientific knowledge for describing the practice of simulation. Moreover, it implies
recognizing the emergence of new kinds of programming languages in computer science, which are
iconographic rather than textual and aesthetical rather than abstract. In this context our article [2] is
composed of two parts:
First Part, FDE refutation: The first part consists of a characterization of the unsatisfactory role of
the classical theory of computation in social simulation. Traditional scientific methodologies often
characterize the concept of program execution as a process of formal inference. To some extent, this
recalcitrant tradition results from conflating the terms “program computation” and “program
execution” into one single meaning, conveying the same ontological status to two fundamentally
distinct processes. Considerations of brevity and simplicity led us to call this tradition the FDE
argument, as per Formal Deduction through Execution. Notwithstanding, our goal is quite the opposite,
namely to demonstrate that simulation shall not be legitimized under the presumption of being an
outcome of a calculus of formal inference. Having this in mind, we will set up the conditions to refute
the FDE argument. The objection to FDE suggests yet another objection to the current methodological
and philosophical thinking in the literature, particularly to the one advocated by Robert Axelrod: our
objection to characterizing simulation as an alternative methodology to deduction and induction.
Second Part, The role of programming languages in simulation: A more informative way to
analyse the methodological and epistemological status of simulation is to examine how simulations are
programmed. The second part of our work discusses the role of programming languages in simulation,
according to intentional accounts of computation. The role of intentional methodologies becomes
crucial once it is realised that, rather than one kind of program and programming language, two kinds
of programs and programming languages are used in the implementation of a simulation: Programs as
text and programs as icons; and languages as abstract machines and languages as aesthetic machines.
The use of abstract languages confirms that the simulation method incorporates both formal and
empirical methodologies. The use of aesthetic languages demonstrates that the simulation method
depends fundamentally on intentional methodologies. While the use of textual programming languages
demonstrates that the logic of simulation incorporates formal and empirical methods, the use of
iconographic languages largely surpasses the use of formal and empirical methodologies. The results of
a simulation are outcomes of experimental setups, but the results of the experiments can hardly be
represented by material conditions of necessity relating facts about the objective behaviours of the
program. The results are appropriately characterized by conditions of intentionality that relate aesthetic
components in the program, negotiated according to a limited level of consensus.
References
[1] David, N., Sichman, J. and Coelho, H. “The Role of Intentional Decision-Making in the Context of
Complex Systems and Information Technologies”. Complexity, Science and Society Conference,
England, Liverpool, University of Liverpool, 11-14th September, 2005.
[2] David, N., Sichman, J. and Coelho, H. "Simulation as Formal and Generative Social Science: The
Very Idea". Gershenson, C., Aerts, D. and Edmonds, B. (Editors). Worldviews, Science and Us:
Philosophy and Complexity, World Scientific (in press), 2006.
[3] David, N., Sichman, J. and Coelho, H.. “The Logic of the Method of Agent-Based Simulation in the
Social Sciences: Empirical and Intentional Adequacy of Computer Programs”, Journal of Artificial
Societies and Social Simulation 8(4), 2005.
[4] David, N., Sichman, J. and Coelho, H. “Intentional Adequacy of Computer Programs as the
Experimental Reference of Agent-Based Social Simulation”. Proceedings of the 4th International
Joint Conference. on Autonomous Agents and Multiagent Systems (AAMAS 05), ACM, pp.1359-
1360, 2005.
[5] Frank, U. and Troitzsch, K. “Epistemological Perspectives on Simulation”. Journal of Artificial
Societies and Social Simulation 8(4), 2005.