BWSS 2008

1st Brazilian Workshop on Social Simulation

Bahia Othon Palace Hotel, Salvador, Bahia, Brazil
October 30th, 2008

(co-located with SBIA 2008 - Brazilian Symposium on Artificial Intelligence)

PROCEEDINGS

Slides of the Invited Talk, by Cristiano Castelfranchi

 

Slides of the Project Presentation, by Cameron Griffith (17.9MB)


Social Simulation is the scientific enterprise through which computational models and tools are employed to computationally study societies and their structures and processes. Specially Artificial Intelligence and Multiagent Systems models are relevant in such context.

On the other hand, Social Simulation may operate as a source of inspiration for theories, models and techniques for AI and MAS, as it heavily draws on the diverse social sciences (anthropology, sociology, political science, economy, government, management, etc.).

This one-day workshop, co-located with SBIA 2008, aims to gather researchers and students in AI, MAS and the various social sciences where Social Simulation has been put to work, in order to further the theoretical and practical issues concerning social simulation, and to leverage the area of Social Simulation in Brazil.

Topics of interest:

-         theoretical foundations of social simulation

-         methods and models for social simulation

-         AI and MAS tools, techniques, models and environments for social simulation

-         applications of social simulation (in social research, government, management, education, etc.)

Organizing committee:

Antônio Carlos da Rocha Costa, UCPel, Brazil
Rafael Heitor Bordini, Durham Univ., UK
Jomi Fred Hübner, FURB, Brazil
Patrícia Restelli Tedesco, UFPE, Brazil
Graçaliz Pereira Dimuro, UCPel, Brazil

Program committee:

Ana Bazzan (UFRGS, Brazil)
Antônio Carlos da Rocha Costa (UCPel, Brazil) - chair
Diana Adamatti (FTEC, Brazil)
Geber Ramalho (UFPE, Brazil)
Graçaliz Pereira Dimuro (UCPel, Brazil)
Gustavo Lugo (UTFPR, Brazil)
Helder Coelho (Univ. Lisbon, Portugal)
Jaime Sichman (USP, Brazil)
João Balsa (Univ. Lisbon, Portugal)
Julita Vassileva (Univ. Saskatchewan, Canada)
Luis Antunes (Univ. Lisbon, Portugal)
Miguel Lozano Ibañez (Univ. Valencia, Spain)
Nuno David (ISCTE, Portugal)
Patrícia Restelli Tedesco (UFPE, Brazil)
Paulo Blikstein (Nortwestern Univ., USA)
Paulo Trigo (ISEL, Portugal)
Ricardo Rodrigo Stark Bernard (UFSC, Brazil)
Roberto da Silva (UFRGS, Brazil)
Stanley Loh (UCPel, Brazil)


 

GENERAL TECHNICAL PROGRAM

08:45 - Invited Talk: Cristiano Castelfranchi (ISTC/CNR)
10:10 - Coffe break
10:30 - Technical Session 1
12:00 - Project Presentation: Cameron Griffith (Indiana Univ., USA)
12:30 - Lunch
14:00 - Technical Session 2
16:00 - Coffe Break
16:20 - Technical Session 3
18:20 - Closing Session

DETAILED TECHNICAL PROGRAM

08:30 - Opening Session

08:45 - Invited Talk: Cristiano Castelfranchi (ISTC/CNR)

10:10 - Coffe break

10:30 - 12:00 Technical Session 1

Paper 1: Applications Simulating a Multi-Agent Electricity Market

Paulo Trigo, Instituto Superior de Engenharia de Lisboa, Portugal

Helder Coelho, Universidade de Lisboa, Portugal.

Abstract. This paper proposes a multi-agent based simulation (MABS) framework to construct an artificial electric power market populated with learning agents. The proposed framework facilitates the integration of two MABS constructs: i) the design of the environmental physical market properties, and ii) the simulation models of the decision-making and reactive agents. The framework is materialized in an experimental setup involving distinct power generator companies which operate in the market and search for the trading strategies that best exploit their generating units resources. The experimental results show a coherent market behavior that emerges from the overall simulated  environment.

Paper 2: Rehearsing Policies for GHGs Emission Control

João Balsa, Fac. Ciências da Universidade de Lisboa, Portugal

Luis Antunes, Faculdade de Ciencias Universidade de Lisboa, Portugal

Luís Moniz, Faculdade de Ciências da Universidade de Lisboa, Portugal

Helder Coelho, Universidade de Lisboa, Portugal.

Abstract. We propose the use of a multiagent-based social simulation approach to help politicians in their task of choosing the best policy/decision when facing complex scenarios. We show how we can use MABS tools an techniques to experiment/rehearse with different scenarios and how this methodology can help decision makers. We use these ideas to develop an application to the problem of GHGs (Greenhouse Gases) emission reduction. We explain why this is a critical problem and stress the importance of our approach to deal with it. We focus here in one of the most relevant instruments that has been used so far -- a market based approach, more specifically the ``carbon market.'''' We illustrate how this type of instruments can be rehearsed, by means of a simulation implemented in the NetLogo framework.

12:00 - Project Presentation: Cameron Griffith (Indiana Univ., USA)

12:30 - Lunch

14:00 - 16:00 Technical Session 2

Paper 3: Methods and Models An experiment on the effect of the strategy representation complexity in an evolutionary n-Players Prisoners Dilemma model

Inacio Lanari Bo, Universidade de São Paulo, Brazil

Jaime Sichman, USP - Universidade de São Paulo, Brazil.

Abstract. This work presents the results of experiments made with a spatial evolutionary model of agents playing the n-Players Prisoner''s Dilemma, using two different ways to represent the agent''s strategies: finite automata and adaptive automata. Since adaptive automata can represent complex strategies that cannot be represented by finite automata, comparative analysis of the co-evolution of strategies using both representations may lead to a better understanding of the role of complex strategies in evolutionary games. Here are presented the differences observed on the total utility obtained by the agents, the speed in which they converge to a nearly-stationary state, and the characteristics of the prevailing strategies.

Paper 4: Contrasting Two Regulation Mechanisms for Personality-based Social Exchange Processes Diego Pereira, Luciano Gonçalves

Graçaliz Dimuro, Universidade Católica de Pelotas, Brazil

Antônio Carlos da Rocha Costa, UCPEL, Brazil.

Abstract. In this paper we review two approaches to the regulation of agent interactions based on Piagets theory of social exchanges. These approaches model a social equilibrium supervisor, that, at each time, recommends certain exchange actions to the agents, in order to lead the interaction towards the equilibrium, regarding the balance of the exchange values involved in the exchanges. One approach uses a centralized supervisor, that has  access to all agents internal state, and give recommendations to lead the agents to an equilibrium in their exchanges. This centralized supervisor uses a Qualitative Interval Markov Decision Process (QI-MDP), to determine the best recommendation for the agents. The other approach is a decentralized one, in which each agent has an equilibrium supervisor internalized in it. In this model, each supervisor in each agent has access to the agents internal state where he is in, but is unable to access the internal states of the other agents. In order to give exchange recommendations to the supervised agent, the internalized supervisor uses BDI (Beliefs, Desires, Intentions) plans derived from the optimal interaction policy provided by a Partially Observable Markov Decision Process (POMDP). We present a qualitative comparison between the two approaches, aiming at the identification of which features of each approach can be used to improve the other one.

Paper 5: Entities and Relations for Agent-Based Modelling of Complex Spatial Systems

Pedro Andrade, INPE, Brazil Antonio Monteiro, Instituto Nacional de

Pesquisas Espaciais, Brazil

Gilberto Câmara, Instituto Naiconal de Pesquisas Espaciais, Brazil.

Abstract. This work presents a contribution towards generalizing the representation of geospatial entities and their relations for simulating complex spatial systems using the agent-based approach. We analyse the works in the literature, and argue that each of the four types of relation is necessary. These relations can be grouped in two classes, placements and neighbourhoods, with likenesses and differences between them. Given that, we define requirements for representing geospatial entities and their relations, and then study six toolkits for ABM (Netlogo, OBEUS, Repast, Swarm, GRSP, and TerraME), analysing their capabilities to address the proposed requirements. Finally, we present our current work and future directions on the development of the TerraME toolkit.

Paper 6: Equation based Models as Formal Specifications of Agent-based Models for Social Simulation: preliminary issues

Antônio Carlos da Rocha Costa, UCPEL, Brazil

Fernanda Jeannes

Ulisses Cava, UCPel, Brazil.

Abstract. This paper presents some issues concerning the idea of taking equation-based simulation models (EBM) as formal, mathematical specifications of agent-based simulation models (ABM) for Social Simulation. The paper tries to identify some of benefits that such point of view could bring to the development of ABM, as well as some of the preliminary problems that an ABM developer has to face, in order to guarantee the credibility of his model. The paper first identifies the benefit of the support for the formal verification of the correction of the ABM, given the correction of the EBM. Then, it identifies a preliminary set of crucial implementation details that are not covered by EBM specifications, and that the simulation developer has to define to make the ABM operational, under the constraint of keeping the ABM model compatible with the EBM. In particular, the two issues of the local vs. global scope of the agents' perceptions and of the degree of personalization of the agents are identified as crucial ones. Some preliminary concepts are proposed to help to solve those two problems.

16:00 - Coffe Break

16:20 - 18:20 Technical Session 3

Paper 7: Applications Evaluation of Collaborative Annotation systems and Simulation of User Behavior on Social Network

João Ferreira, ISEL, Portugal

Paulo Trigo, Instituto Superior de Engenharia de Lisboa, Portugal.

Helder Coelho, Universidade de Lisboa, Portugal. 

Abstract. In this paper we propose an approach for modeling the user annotation behavior based on a simulated query feedback. The annotation skills are the basis for the collaborative annotation systems, which compare the users information needs (expressed in a query), with the annotations (made by users) that classify the documents. The evaluation of annotation systems is complex due to: i) the difficulty in closing the environment, ii) the number and diversity of users, and iii) the language subjectivity. Our simulation explores the relation between the user society and their annotation skills to better understand how it affects the systems retrieval accuracy. This approach can also be applied to measure the systems performance in information retrieval systems.

Paper 8: Efficiency of the Emergence of Consensus in Complex Networks assessing force influence

Paulo Urbano, Faculdade de Ciências da Universidade de Lisboa, Portugal

João Balsa, Fac. Ciências da Universidade de Lisboa, Portugal

Luis Antunes, Faculdade de Ciencias Universidade de Lisboa, Portugal

Luís Moniz, Faculdade de Ciências da Universidade de Lisboa, Portugal.

Abstract. Interactions between agents in multi-agent systems have an inherent potential for conflict and must be coordinated. The adhesion to uniform behaviour is one way of coordinating actions: social conventions and lexicons are good examples of coordinating systems, where uniformity promotes shared expectations of behaviour and shared meanings. This paper deals with the emergence of a uniform collective choice, a consensus, inside a population of artificial agents. The efficiency of the formation of a uniform shared decision or choice is an important issue. The nature of interactions and also the nature of society configurations may promote or inhibit consensual emergence. We study the efficiency of uniform decision formation along two dimensions: rules of interaction and network topologies. We compare two different interaction behaviours: the well know and used Highest Cumulative Reward, which is a kind of reinforcement learning behaviour, against a recent behaviour named Recruitment based on Force. We also compare those interaction behaviours along five types of social link networks: fully connected, regular, random, scale-free and small-world. Simulating Argumentation about Exchange Values in

Paper 9: Multi-Agents Interactions

Márcia Franco, Universidade Federal do Rio Grande do Sul, Brazil

Antônio Carlos da Rocha Costa, UCPEL, Brazil

Helder Coelho, Universidade de Lisboa, Portugal.

Abstract. This article presents two dialogue protocols to support argumentation about the exchange values involved in multi-agents interactions. In this work, we adopt the Piaget''s theory of social exchanges, where as interaction is an exchange of services between agents, such that they agents assign subjective, qualitative values to the actions and objects that they exchange during the interaction. The protocols enable the agents to argue with each other about the exchange values. The agents present characteristics related to the social power and personality traits. We show how these characteristics are considered in the reasoning of the agents, and how it can influence the actions of the agents during the interactions.

Paper 10: Simulations of Disease Dissemination Using the Vidya Multi-Agent Systems Platform

Marcelo Pita

Fernando Buarque de Lima Neto, University of Pernambuco, Brazil.

Abstract. This paper simulates the dynamics of a virtual disease disseminated on a population made of intelligent agents (called Jivas) in the Vidya multi-agent system platform. Vidya was originally proposed as a strategy and god game in which player is responsible for supplying intuitions to a Jivas clan, aiming at helping it to survive in a complex and adaptive environment. This environment is inhabited not only by Jivas, but also by many other types of artificial lives that compete by natural resources. This combination of characteristics motivated us to use the Vidya game as a social simulation and multi-agent systems platform, where fairly complex social phenomena and strategies can be investigated. In a previous work the Vidya platform has been used to simulate egoism and altruism, revealing interesting coherent dynamics for artificially motivated social behaviors. In this paper we have incorporated in the Jivas intelligent decision module

one additional decision variable, which is the presence (or lack) of disease. Results obtained in simulations have shown emergent change in social behaviors of Jivas social aggregation, mostly related to the disease contamination and dissemination. We argue that this platform may be considered in the future as a base for plausible agent-based social simulations that might be used for supporting public policies in heath care and other relevant social areas.

18:20 Closing Session