Diana Francisca Adamatti

Modeling Role Interactions in a Social Organization for the Simulation of the Social Production and Management of Urban Ecosystems: The Case of San Jerónimo Vegetable Garden of Seville, Spain

This paper presents some preliminary results obtained in the modeling of a multiagent system for the simulation of the social production and management of a urban ecosystem, in particular, the project of the San Jerónimo Vegetable Garden of city of Seville, Spain. We introduce a study regarding the interactions between agent roles in this particular social organization. For that, we use Activity Diagrams of UML, which provide a clear visualization of the communication between agent roles and allow the identification of communication protocols used by the agents. Furthermore, we show an initial proposal for the encapsulation of those protocols in Cart Ago artifacts, presenting a more modular approach for agent communication in multiagent systems.

Analyzing the Problem of the Modeling of Periodic Normalized Behaviors in Multiagent-Based Simulation of Social Systems: The Case of the San Jerónimo Vegetable Garden of Seville, Spain

This paper presents some results obtained through the modeling of a multiagent system for the simulation of production and social management processes of an urban ecosystem: the San Jeronimo Vegetable Garden (HSJ) of Seville, Spain. The social organization of HSJ is based on the performance of periodic routines by the organizational roles, and also on periodic norms that regulates their behaviors. For the modeling this kind of periodicity, that are commonly observed in social system, we used a combination of tools to offer a suitable solution, as the MOISE+ (part of JaCaMo platform) and the MSPP (Modeling and Simulation of Public Policies) framework. Although those tools separately present limitations for the modeling of periodic actions and norms associated to the performance of those actions, they can be used in a combined way, where the norms are specified in the MSPP framework, which support periodicity, and the normalized routines in the MOISE+ model.

Interdisciplinary Applications of Agent-Based Social Simulation and Modeling

Social simulation can be a difficult discipline to encompass fully. There are many methods, models, directions, and theories that can be discussed and applied to various social sciences. Anthropology, sociology, political science, economy, government, and management can all benefit from social simulation. Interdisciplinary Applications of Agent-Based Social Simulation and Modeling aims to bring a different perspective to this interdisciplinary topic. This book presents current discussions and new insights on social simulation as a whole, focusing on its dangers, pitfalls, deceits, and challenges. This book is an essential reference for researchers in this field, professionals using social simulation, and even students studying this discipline.

Extending the Computational Study of Social Norms with a Systematic Model of Emotions

It is generally recognized that the use of emotions plays an important role in human interactions, for it leads to more flexible decision-making. In the present work, we extend the idea presented in a paper by Castelfranchi, Conte, and Paolucci, by employing a systematic and detailed model of emotion generation. A scenario is described in which agents that have various types of emotions make decisions regarding compliance with a norm. We compare our results with the ones achieved in previous simulations and we show that the use of emotions leads to a selective behavior which increases agent performance, considering that different types of emotions cause agents to have different acting priorities.

Simulating Reputation with Regulatory Policies: The Case of San Jerónimo Vegetable Garden, Seville, Spain

This paper presents a reputation model applied to a multi-agent system for simulating regulatory policies and reputation of the social organization of San Jeronimo Vegetable Garden, located in Seville, Spain. We have used BDI agents with fuzzy beliefs for the investment and satisfaction analysis of services, as well as a reputation model as a performance measure of their activities within the project.

Analysing the Influence of the Cultural Aspect in the Self-Regulation of Social Exchanges in MAS Societies: An Evolutionary Game-Based Approach

Social relationships are often described as social exchanges, understood as service exchanges between pairs of individuals with the evaluation of those exchanges by the individuals themselves. Social exchanges have been frequently used for defining interactions in MAS. An important problem that arises in the context of social simulation and other MAS applications is the self-regulation of the social exchange processes, so that the agents can achieve/maintain the equilibrium of the exchanges by themselves, guaranteing the continuation of the interactions in time. Recently, this problem was tackled by defining the spatial and evolutionary Game of Self-Regulation of Social Exchange Processes (GSREP), implemented in NetLogo, where the agents evolve their exchange strategies by themselves over time, performing more equilibrated and fair interactions. The objective of this paper is to analyse the problem of the self-regulation of social exchange processes in the context of a BDI-based MAS, adapting the GSREP game to Jason agents and introducing a cultural aspect, where the society culture, aggregating the agents’ reputation as group beliefs, influences directly the evolution of the agents’ exchange strategies, increasing the number of successful interactions and improving the agents’ outcomes in interactions.

An Overview of Social Simulation Research in Brazil

Presented as a panel at the Third Brazilian Workshop on Social Simulation (BWSS 2012), held in Curitiba, Brazil, on October 20th. 2012, this paper presents an overview of the current research on social simulation in Brazilian research groups.

Trust Transference on Social Exchanges Among Triads of Agents Based on Dependence Relations and Reputation

This paper proposes the addition of a third agent to the model proposed by Piaget to Social Exchanges. This agent, called an Intermediary Agent, may outsource a service in favor of another agent. This situation can be used to develop a social exchange model for triads of agents in order to evaluate the process of trust transfer between agents who are not familiar with each other, i.e., they have never interacted directly, just by the intermediary agent. The trust transfer analysis is based on exchange value, reputation and dependence relationship concepts, all of which are analyzed interdependently. This way, it complements the Piaget model, generating a contribution to the study of non-economic aspects of the exchange process. The generated information can be used to guide agents’ decisions about partner choice in future exchanges. Additionally, it provides a starting point to understanding the agents’ behavior in interactions among more than three agents.

Multi-Agent-Based Simulation of Mycobacterium Tuberculosis Growth

Tuberculosis is an infectious disease that still causes many deaths around the world nowadays. It is caused by the M. tuberculosis bacillus. The study of the growth curve of this infectious organism is relevant as it has wide applications in tuberculosis research. In this work a Multi-Agent-Based Simulation is proposed to pursue the reproduction in silico of the observed in vitro M. tuberculosis growth curves. Simulation results are qualitatively compared with growth curves obtained in vitro with a recent proposed methodology. The results are promising and indicate that the chosen simulation methodology has the potential to serve as a platform for testing different bacterial growing behaviour as well as bacteria growth under different conditions.

Self-regulation of Social Exchange Processes: A Model Based in Drama Theory

This paper presents a dramatic model for self-regulation of social exchange processes in multiagent systems, based on the concepts of Drama Theory. The model has five phases of dramatic resolution, which involve feelings, emotions, trust and reputation. Agents with different social exchange strategies interact each other in order to maximize their strategy-based fitness functions. The objective is to obtain a more natural model than the ones existing in the literature, which are based on (partially observable) Markov decision processes or in game theory, so that it can be applied in real-world applications. We aim at promoting more balanced and fair multiagent interactions, increasing the number of successful social exchanges and, thus, promoting the continuity of social exchanges.