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

An Analysis of the Insertion of Virtual Players in GMABS Methodology Using the Vip-JogoMan Prototype

The GMABS (Games and Multi-Agent-Based Simulation) methodology was created from the integration of RPG and MABS techniques. This methodology links the dynamic capacity of MABS (Multi-Agent-Based Simulation) and the discussion and learning capacity of RPG (Role-Playing Games). Using GMABS, we have developed two prototypes in the natural resources management domain. The first prototype, called JogoMan (Adamatti et. al, 2005), is a paper-based game: all players need to be physically present in the same place and time, and there is a minimum needed number of participants to play the game. In order to avoid this constraint, we have built a second prototype, called ViP-JogoMan (Adamatti et. al, 2007), which is an extension of the first one. This second game enables the insertion of virtual players that can substitute some real players in the game. These virtual players can partially mime real behaviors and capture autonomy, social abilities, reaction and adaptation of the real players. We have chosen the BDI architecture to model these virtual players, since its paradigm is based on folk psychology; hence, its core concepts easily map the language that people use to describe their reasoning and actions in everyday life. ViP-JogoMan is a computer-based game, in which people play via Web, players can be in different places and it does not have a hard constraint regarding the minimum number of real players. Our aim in this paper is to present some test results obtained with both prototypes, as well as to present a preliminary discussion on how the insertion of virtual players has affected the game results.Role-Playing Games, Multi-Agent Based Simulation, Natural Resources, Virtual Players

DEPINT: Dependence-Based Coalition Formation in an Open Multi-Agent Scenario

This paper presents the main features and some simulation results for the DEPINT system, a multi-agent system conceived to illustrate some essential aspects of a social reasoning mechanism (Sichman, 1995), based on the notion of social dependence (Castelfranchi et al., 1992). This social reasoning mechanism is considered to be an essential building block of really autonomous agents, immersed in an open multi-agent system (MAS) context, i.e., where agents may dynamically enter or leave the society, without any global control. As the adaptation of an agent in such a scenario concerns, dependence relations allow an agent to know which of his goals are achievable and which of his plans are feasible at any moment. This way, an agent may dynamically choose a goal to pursuit and a plan to achieve it, being sure that every skill needed to accomplish the selected plan is available in the society. Concerning coalition formation, this model introduces the notion of dependence situation, which allows an agent to evaluate the susceptibility of other agents to adopt his goals, since agents are not necessarily supposed to be benevolent and therefore automatically adopt the goals of each other. Finally, as regardsbelief revision, the social reasoning mechanism allows an agent to detect that his representation of the others is inconsistent. Because agents' interactions are guided by their information about the others, it is exactly during these interactions that they may detect that this information is either incorrect or incomplete, and eventually revise it.Emergent Organizations, Dependence-Based Interaction, Social Behaviour, Open Systems

Report on the Multi-Agent Based Simulation (MABS) 2002 Workshop, Bologna, Italy, July 2002

Multi-Agent Based Simulation (MABS) workshop is a key event for the researchers working in the field of agent based simulations because it favours the encounter between researchers woking on applied social simulations who are interested on computer science aspects (architectures, platforms, methodologies) on the one hand, and computer scientists willing to understand how agent based models can be modelled from the observation of the real world.Interdisciplinarity, methodologies

The Structure and Logic of Interdisciplinary Research in Agent-Based Social Simulation

This article reports an exploratory survey of the structure of interdisciplinary research in Agent-Based Social Simulation. One hundred and ninety six researchers participated in the survey completing an on-line questionnaire. The questionnaire had three distinct sections, a classification of research domains, a classification of models, and an inquiry into software requirements for designing simulation platforms. The survey results allowed us to disambiguate the variety of scientific goals and modus operandi of researchers with a reasonable level of detail, and to identify a classification of agent-based models used in simulation. In particular, in the interdisciplinary context of social-scientific modelling, agent-based computational modelling and computer engineering, we analyse the extent to which these paradigmatic models seem to be mutually instrumental in the field. We expect that our proposal may improve the viability of submitting, explaining and comparing agent-based simulations in articles, which is an important methodological requirement to consolidate the field. We also expect that it will motivate other proposals that could further validate, extend or change ours, in order to refine the classification with more types of models.Interdisciplinary Research, Social-Scientific Models, Multiagent-Based Models, Verification and Validation