Showing papers in "Journal of Artificial Societies and Social Simulation in 2001"

Role-playing games for opening the black box of multi-agent systems: method and lessons of its application to Senegal River Valley irrigated systems

Abstract: Multi-agent systems and role playing games have both been developed separately and offer promising potential for synergetic joint use in the field of renewable resource management, for research, training and negotiation support. While multi-agent systems may give more control over the processes involved in role playing games, role playing games are good at explaining the content of multi-agent systems. The conversion of one tool to another is quite easy but organisation of game sessions is more difficult. Both these tools have been used jointly in a fully described experiment in the Senegal river valley for issues of co-ordination among farmers. Role-playing games first enabled us to work on the validation of the MAS. Subsequently, the combination of both tools has proved to be an effective discussion support tool.

Innovation networks-a simulation approach

Abstract: A multi-agent simulation embodying a theory of innovation networks has been built and used to suggest a number of policy-relevant conclusions The simulation animates a model of innovation (the successful exploitation of new ideas) and this model is briefly described Agents in the model representing firms, policy actors, research labs, etc each have a knowledge base that they use to generate ‘artefacts’ that they hope will be innovations The success of the artefacts is judged by an oracle that evaluates each artefact using a criterion that is not available to the agents Agents are able to follow strategies to improve their artefacts either on their own (through incremental improvement or by radical changes), or by seeking partners to contribute additional knowledge It is shown though experiments with the model's parameters that it is possible to reproduce qualitatively the characteristics of innovation networks in two sectors: personal and mobile communications and biotechnology

Do irregular grids make a difference? Relaxing the spatial regularity assumption, in cellular models of social dynamics

Abstract: Three decades of CA-modelling in the social sciences have shown that the cellular automata framework is a useful tool to explore the relationship between micro assumptions and macro outcomes in social dynamics. However, virtually all CA-applications in the social sciences rely on a potentially highly restrictive assumption, a rectangular grid structure. In this paper, we relax this assumption and introduce irregular grids with variation in the structure and size of neighbourhoods between locations in the grid. We test robustness of two applications from our previous work that are representative for two broad classes of CA models, migration dynamics and influence dynamics. We tentatively conclude that both influence dynamics and migration dynamics have important general properties that are robust to variation in the grid structure. At the same time, we find in both examples substantively interesting implications of the irregular grid that could not be identified with a regular grid structure.

Introducing Emotions into the Computational Study of Social Norms: A First Evaluation.

Abstract: It is now generally recognised that emotions play an important functional role within both individuals and societies, thereby forming an important bond between these two levels of analysis. In particular, there is a bi-directional interrelationship between social norms and emotions, with emotions playing an instrumental role for the sustenance of social norms and social norms being an essential element of regulation in the individual emotional system. This paper lays the foundations for a computational study of this interrelationship, drawing upon the functional appraisal theory of emotions. We describe a first implementation of a situated agent architecture, TABASCOJAM, that incorporates a simple appraisal mechanism and report on its evaluation in a well-known scenario for the study of aggression control as a function of a norm, that was suitably extended. The simulation results reported in the original aggression control study were successfully reproduced, and consistent performances were achieved for extended scenarios with conditional norm obeyance. In conclusion, it is argued that the present effort indicates a promising lane towards the necessary abandonment of logical models for the explanation and simulation of human social behaviour.

Intelligent Social Learning.

Abstract: One of the cognitive processes responsible for social propagation is social learning, broadly meant as the process by means of which agents' acquisition of new information is caused or favoured by their being exposed to one another in a common environment Social learning results from one or other of a number of social phenomena, the most important of which are social facilitation and imitation In this paper, a general notion of social learning will be defined and the main processes that are responsible for it, namely social facilitation and imitation, will be analysed in terms of the social mental processes they require A brief analysis of classical definitions of social learning is carried on, showing that a systematic and consistent treatment of this notion is still missing A general notion of social learning is then introduced and the two main processes that may lead to it, social facilitation and imitation, will be defined as different steps on a continuum of cognitive complexity Finally, the utility of the present approach is discussed The analysis presented in this paper draws upon a cognitive model of social action (cf Conte & Castelfranchi 1995; Conte 1999) The agent model that will be referred to throughout the paper is a cognitive model, endowed with mental properties for pursuing goals and intentions, and for knowledge-based action To be noted, a cognitive agent is not to be necessarily meant as a natural system, although many examples examined in the paper are drawn from the real social life of humans Cognitive agents may also be artificial systems endowed with the capacity for reasoning, planning, and decision-making about both world and mental states Finally, some advantages of intelligent social learning in agent systems applications are discussed Keywords:

What is Ascape and Why Should You Care

Abstract: Ascape is a framework designed to support the development, visualization, and exploration of agent based models. In this article I will argue that agent modeling tools and Ascape, in particular, can contribute significantly to the quality, creativity, and efficiency of social science simulation research efforts. Ascape is examined from the perspectives of use, design, and development. While Ascape has some unique design advantages, a close examination should also provide potential tool users with more insight into the kinds of services and features agent modeling toolkits provide in general.

Clustering and fighting in two-party crowds : Simulating the approach-avoidance conflict

Abstract: When two large groups of people meet in the same space, many outcomes are possible, depending on the types of groups and the occasion. These outcomes range from a peaceful mingling of the two groups to the occurrence of fights and riots. Because the group processes leading to these outcomes are difficult to study experimentally, we developed a multi-agent simulation model in which the approach-avoidance conflict has been formalised in simulated actors. We worked with three different kinds of agents: hardcore, hangers-on and bystanders, the difference between them consisting in the frequency with which they scan their surroundings. Data on clustering, and 'fights' are presented for 80 simulation runs, in which group size, size symmetry and group composition were varied. The conclusions are that fights especially happen in asymmetrical large groups with relatively large proportions of hardcore members. Moreover, it appears that it are especially the hardcore group and the hangers-on that attack other agents, whereas bystanders are The paper ends with a discussion on the validity of these findings, leading us to conclude that basic aspects of rioting behaviour are quite realistically represented in our simulation model.

ABLooM: Location behaviour, spatial patterns, and agent-based modelling

Abstract: This paper presents an Agent-based LOcation Model (ABLOoM). ABLOoM simulates the location decisions of two main types of agents, namely households and firms. The model contains multiple interactions that are crucial in understanding land use changes, such as interactions of agents with other agents, of agents with their environment and of agents with emerged patterns. In order to understand the mechanisms that are at the basis of land use changes and the formation of land use patterns, ABLOoM allows us to study human behaviour at the microlevel in a spatial context. The models, which include economic theory, aspects of complexity theory and decision rules, show that it is possible to generate macrolevel land use patterns from microlevel spatial decision rules.

A bargaining model to simulate negotiations between water users

Abstract: The French water law of 1992 requires that regulations on water use and water management be negotiated collectively and locally in each river sub-basin. Decision-makers therefore need new tools to guide the negotiation process which will take place between water users. A formal computable bargaining model of multilateral negotiations is applied to the Adour Basin case, in the South West of France, with seven aggregate players (three farmers, two "environmental lobbies", the water manager, the taxpayer) and seven negotiation variables (three individual irrigation quotas, the price of water, the sizes of three dams). The farmers' utility functions are estimated with hydraulic and economic models. A sensibility analysis is conducted to quantify the impact of the negotiation structure (political weights of players, choice of players...) on game outcomes. The relevance of the bargaining models as negotiation-support tools is assessed.

Modelling the Emergence of Possession Norms using Memes

Abstract: In this paper we study the emergence and the effects of a possession norm in an artificial society. We link the study of norms and the concept of memes as put forward by Richard Dawkins. Normative behaviour is modelled using memes as carriers for certain behaviours. For our simulations we extend the sugarscape model from Epstein and Axtell (1996) and give the agents the possibility to claim possession of a

History-Friendly models: An overview of the case of the Computer Industry.

Abstract: This paper presents and discusses the methodological rationale, the basic structure and some first results of a new approach to the analysis of processes of industry evolution: "history-friendly" models, concerning the history of the computer industry. The specific purpose of this paper is to evaluate in more general terms the potential and limits of this approach, rather than the formal structure or results of a particular case. The paper illustrates first the philosophy beneath the use of "history-friendly" models. Then, after a brief summary of the main stylized facts about the evolution of the computer industry and of the main theoretical issues raised up by our investigation, we go on presenting the structure of the model. We then discuss the main results and some preliminary exercises involving different hypotheses on agents' behavior (strategies of product diversification) and policy issues.

Simulating the Evolution of Localised Industrial Clusters - An Identification of the Basic Mechanisms.

Abstract: Localised industrial clusters have received much attention in economic research in the last decade They are seen as one of the reasons for the economic success of certain regions in comparison to others This paper studies the evolution of such industrial clusters To this end, a spatial structure of regions is set up and the entry, exit, and growth of firms within these regions is modelled and studied with the help of simulations Several mechanisms that are often stated to be important in the context of localised industrial clusters are explicitly modelled The influence of these mechanisms on the geographical concentration of industries is studied

Intervening to Achieve Co-operative Ecosystem Management: Towards an Agent Based Model.

Abstract: We propose an advanced agent-based modelling approach to ecosystem management, informed and motivated by consideration of the Fraser River watershed and its management problems. Agent-based modelling is introduced, and a three-stage computer-based research programme is formulated, the focus of which is on how best to intervene to cause stakeholders to co-operate effectively in ecosystem management, and on the objective discovery and comparison of intervention strategies by way of computer experimentation. The agent-based model outlined is technically relatively complex, and several potential difficulties in its detailed development are discussed. Types of ecosystem intervention strategy that might plausibly be discovered or recommended by the model are projected and compared with those currently advocated in the literature.

Agent-Based modelling, game theory and natural resource management issues

Abstract: This special issue of JASSS presents a set of papers selected from a workshop held in Montpellier in March 2000[1] The objective was to stimulate discussions between researchers who use and develop game theory (GT) or multi-agent systems (MAS) especially in the field of natural resource management and environment. (Resume d'auteur)

Consensus and cohesion in simulated social networks

Abstract: Social structure emerges from the interaction and information exchange between individuals in a population. The emergence of groups in animal and human social systems suggests that such social structures are the result of a cooperative and cohesive society. Using graph based models, where nodes represent individuals in a population and edges represent communication pathways, we simulate individual influence and the communication of ideas in a population. Simulations of Dunbar's hypothesis (that natural group size in apes and humans arises from the transition from grooming behaviour to language or gossip) indicate that transmission rate and neighbourhood size accompany critical transitions of the order proposed in Dunbar's work. We demonstrate that critical levels of connectivity are required to achieve consensus in models that simulate individual influence.

From Social Monitoring to Normative Influence

Abstract: This paper is intended to analyse the concepts involved in the phenomena of social monitoring and norm-based social influence for systems of normative agents. These are here defined as deliberative agents, representing norms and deciding upon them. Normative agents can use the norms to evaluate others' behaviours and, possibly, convince them to comply with norms. Normative agents contribute to the social dynamics of norms, and more specifically, of norm-based social control and influence. In fact, normative intelligence allows agents to 1. Check the efficacy of the norms (the extent to which a norm is applied in the system in which it is in force), and possibly 2. Urge their fellows to obey the norms. The following issues are addressed: What is norm-based control? Why and how do agents exercise control on one another? What role does it play in the spread of norms?

Competition as a Test of Hypotheses: Simulation of Knowledge-generating Market Processes.

Abstract: Hayek's well-known evolutionary concept of "competition as a discovery procedure" can be characterized as a parallel process of experimentation, in which rivalrous firms generate and test hypotheses about the best way to fulfill the consumers' preferences Through this permanent process of variation and selection of hypotheses (innovation / imitation) a process of knowledge accumulation can take place The central aim of our paper is to model the basic Hayekian learning mechanism, which consists of experimentation and mutual learning, and to ask for determinants of the rapidity of knowledge accumulation In our multilevel simulation model, on the micro level, firms create new hypotheses through mutation On the macro level, on the market, these hypotheses meet and the best firm is determined All firms then imitate the best firm In our model, 100 of these periods which consist of an innovation and an imitation phase are simulated We presume that decentrality is crucial for the working of the knowledge-generating process, because a larger number of independently innovating firms leads to more experimentation We investigate into the impact of firm concentration, the impact of the decentralization of firms, as well as the impact of impediments in imitation like lock-ins on the growth rate of knowledge accumulation Our simulation results show that the number of firms is positively correlated with the rapidity of knowledge accumulation suggesting a new argument for a critical assessment of mergers in competition policy

Dynamics in Human and Primate Societies: Agent-Based Modeling of Social and Spatial Processes Edited by Timothy A. Kohler and George J. Gumerman .

Abstract: social processes, 359, 366 examples of, 359-366 adaptation, 7, 8 evolving, 8 trajectory of, 378 See also coadaptation adaptation and coevolution models, 364-365 learning in, 364 adaptive agents, 208, 214, 216 adaptive dynamics, 87 adaptive landscapes, 220 agency, 109, 208 agent design, 93 anthropomorphic beliefs, 94 beliefs, 94-95 egocentric vs. sociocentric, 101 genotypes, 111, 126-129 in MAGICAL software, 110-114 memes, 100 subagents, 102 agent-based artificial societies, 89-91, 102 abilities of, 91 advantages of, 98 cultural preconceptions in, 99-100 EOS project, 91, 92, 360, 380 hunter-gatherer project, 92-93 methodological problems, 98-102 role of emotions in, 95-98 SCENARIO-3, 95, 380 agent-based modeling, 1, 2, 9-11, 13, 14, 48, 52, 71, 89-90, 102, 139, 179, 180, 225, 383 advantages of, 48, 69, 201-202, 374 agent design in, 110 of ancient Egyptian society, 276 challenges to, 379 emergence in, 69 usefulness of, 12 vs. agent-based artificial societies, 98 vs. equation-based modeling, 69-71 See also abstract social processes agent-based models. See adaptation and coevolution models; Artificial Anasazi model; Bali model; comparative advantage models; computer simulations; hierarchi-

Modelling the emergence of resource-sharing conventions: an agent-based approach

Abstract: This paper presents an agent-based simulation framework for the analysis of the emergence of resource-sharing conventions. The model is based on Sugden's article entitled Spontaneous order , which looks at the conditions under which conventions regarding access to a natural resource become established. The aim of the model is to explore the potential of agent-based modelling for the analysis of these questions. First, the structure of a simulation model based on the example of driftwood collection used by Sugden is presented. Second, simulations of various scenarios about the behavioural rules followed by agents are described, and simulation results are presented. The paper concludes with a brief discussion of the advantages of agent-based models for analysing social processes such as the emergence of conventions regulating access to natural resources.

Technology and culture: The dissemination and the potential 'lock-in' of new technologies

Abstract: How do technological innovations change the patterns of their cultural diffusion in socio-economic networks? Cellular automata enable us to show Arthur's (1988) model of a potential 'lock-in' of a new technology in terms of dominant colours on the screen. The 'lock-in' effects can be combined with local learning, network effects, and more complex dynamics. Recursive and interaction terms can thus be declared separately in the construction of a simple, but non-linear model of technological development and innovation. This enables us to specify conditions for a 'break-out' or a 'deadlock' between competing technologies. Using Axelrod's (1997) simulation model of 'cultural dissemination' as another network effect, it will be shown that the cultural assimilation of a new technology can co-evolve with the 'lock-in' of a dominant technology. This effect can be annihilated by the further development of the communication with an emerging dimension. Implications for technology and innovation policies will be specified.

The creation of a reputation in an artificial society organised by a gift system

Abstract: This paper describes simulations in an artificial society in which autonomous agents exchange gifts In this society agents perform simple acts that are looked at by the others and are analysed so that a common image is created for each agent (a reputation) The model is based on numerous descriptions of non-merchant exchange systems, which are very interesting for ethnologists as well as for economists: they appear to be important for circulation of goods and to insure the reproduction of social links and values In the system built the agents must make a gift at each time-step There exist two kinds of gifts and two corresponding kinds of reputation: the agents either give to share or to be prestigious Since gifts are received according to status, receiving a gift is as important for a reputation as making one Each agent is characterised by its "motivation" to acquire the reputation of being a sharing agent or a prestigious agent It is also characterised by its "esteem", to decide if it will be able to do the gift it wants to do for a time-step These two characteristics of an agent can be stable during the simulation, but can also evolve according to its history We study here the different patterns that can appear in the societies, in terms of generation of reputation, and of histories over time A huge range of these patterns can be observed, depending on the choice made for the parameters In some cases the agents cannot be individually distinguished, in other cases they can: but, in any case any individual behaviours that emerge have to be sustained by a collective specification that points out more or less the way agents value each reputation (Resume d'auteur)

Narrative Intelligence from the Bottom Up: A Computational Framework for the Study of Story-Telling in Autonomous Agents

Abstract: This paper addresses Narrative Intelligence from a bottom up, Artificial Life perspective. First, different levels of narrative intelligence are discussed in the context of human and robotic story-tellers. Then, we introduce a computational framework which is based on minimal definitions of stories, story-telling and autobiographic agents. An experimental test-bed is described which is applied to the study of story-telling, using robotic agents as examples of situated, autonomous minimal agents. Experimental data are provided which support the working hypothesis that story-telling can be advantageous, i.e. increases the survival of an autonomous, autobiographic, minimal agent. We conclude this paper by discussing implications of this approach for story-telling in humans and artifacts.

Game theory: limitations and an alternative

Abstract: The purpose of this paper is to describe current practice in the game theory literature, to identify particular characteristics that ensure the literature is remote from anything we observe and to demonstrate an alternative drawn from agent based social simulation. The key issue is the process of social interaction among agents. A survey of game theoretic models found no models representing interaction among more than three agents, though sometimes more agents were involved in a round robin tournament. An ABSS model is reported in which there is a dense pattern of interaction among agents and outputs from the model are shown to have the same statistical signature as high-frequency data from competitive retail and financial markets. Moreover, the density of agent interaction is seen to be necessary both to obtain the validating statistical signature and for simulated market efficiency. As far as competitive markets are concerned, game theoretic models evidently assume away the source of the properties observed in real high frequency data and also the properties required for market efficiency.

Information Structure and Behaviour of a Textile Industrial District.

Abstract: This article presents a model of the structure of the information flows that underlie the creation of production chains between thousands of small textile firms located in Prato, central Italy. Contrary to most textile industry of western Europe and north America, Prato did not die out once average salaries in the region rose towards the world's highest. The reason is that Prato was able to switch from a competitive advantage based on low prices to a competitive advantage based on the aesthetical features and variety of textiles. Analysis of the structure of production chains can explain the performance of this distributed production system throughout its evolution. The model reconstructs interactions of ten types of Pratese firms from 1946 to 1993 on a scale 1:1.

Evaluating the impact of increasing memory on agent behaviour:Adaptive patterns in an agent based simulation of subsistence

Abstract: This is an interim report on a set of ongoing agent-based simulation experiments. The main goal of the experiments is to evaluate the impact of varying memory capacities on the ability of agents to adapt to given subsistence environments and resource landscapes. The results so far suggest that increasing the number of events which an agent can use in decision making does not directly lead to an increase in the agent's ability to adapt to an environment. Variable memory capacity, however, does lead to diversification of agent behaviour patterns in a given environment. The results also suggest that more permissive environments allow agents with greater memory to show a greater diversity of behaviour than similar agents in more restrictive environments. These early results are providing the starting hypotheses which are at the core of a larger set of experiments presently being carried out. The simulation engine and source code are available from the author.

Bad Arguments in the Comparison of Game Theory and Simulation in Social Studies.

Abstract: The aim of this note is to clarify and to correct some arguments which are used in the debate about the comparison of discrete social simulation with other methodologies used in the study of social phenomena, notably those of game theory. Though part of what will be said also applies to non-discrete simulation, the arguments are investigated only as far as the discrete case is concerned. The main claims against each of both scientific approaches are considered in particular, i.e. "impossibility" of game theory and "unsoundness" of simulation studies. Regarding the latter, arguments are presented that items occurring in simulation studies correspond to the formal constituents of a scientific theory, and thus a comparison of both approaches on the same level is justified. The question whether a superiority of one of the two approaches can be stated is illuminated in the light of four dimensions: empirical adequacy, theoretical fruitfulness, social relevance, and simplicity. This leads to the conclusion that both claims are unjustified and should be avoided in the debate about the role and merits of social simulation.

Six Levels of Complexity; a Typology of Processes and Systems

Abstract: A closer examination of the position of processes and systems on a scale of complexity is a precondition for the simulation of (biotic and) social processes and systems. It is possible to distinguish 6 levels: 1st level of complexity: the process takes place mainly between 2 concrete participants (simple movement). Control by the environment, not yet a system (solidum). 2nd level of complexity: the process orders the movements, it is horizontally (temporally) oriented, and passes in each case through 4 stages (movement project). The system is the sum of the elements and orders itself through its elements (equilibrium system). 3rd level of complexity: the process distributes energy (demanded products), it is vertically (between superior and inferior environment, market) oriented and passes in each case through 4 bonding levels (flow process). The system is more than the sum of its elements, it regulates itself as a whole (flow-equilibrium system). 4th level of complexity: the process converts energy into products, it is horizontally (temporally) oriented, and passes in each case through 8 stages (7 by overlapping) (process sequence), it is based on division of labour. Each system organises itself structurally as a whole (non-equilibrium system). 5th level of complexity: the process is vertically (hierarchically) oriented and in each case passes through 8 hierarchical levels (7 by overlapping)(hierarchical process). Each system generates itself structurally by organising its elements and subsystems (hierarchic system). 6th level of complexity: process is horizontally (spatially) oriented, and probably passes 16 spheres (13 by overlapping) in each case (universal process, universal system). Each system within the spheres generates itself materially: autopoiesis.

Evolutionary Perspectives on Simulations of Social Systems.

Abstract: The first part discusses modeling social systems from an evolutionary perspective. The main problems for evolutionary modeling, differentiation and structural change, possible approaches to these problems as well as hindrances to successful modeling are discussed. It is found that concepts of change processes need to be delimited more clearly, and combinatory emergence should be given more attention. Likewise theorizing on evolutionary processes needs to be broadened to be able to capture social phenomena. The results are used to evaluate simulation approaches for evolutionary processes in social systems: Classifier Systems, Genetic Algorithms, Evolution Strategies, Evolutionary Programming, Genetic Programming and simulations suites/programs are considered. For the latter some useful resources on the web are indicated.

Lake Anderson Revisited by Agents.

Abstract: In our paper, we replicate simulation experiments carried out some 30 years ago by Jay M. Anderson who then tried to find out which measures should be taken to avoid the eutrophication of a lake. In his DYNAMO model, he simulated the development of a lake under cultural eutrophication, i.e. mainly by the discharge of fertilisers from agriculture. He designed a number of policies and applied them as an experimenter. In our model, some of the policies suggested by Anderson are taken by a government (or, alternatively, by a number of regional governments) who are in charge of the region(s) around the lake. We define rules which the authorities apply when they find that some of the variables which describe the state of the lake exceed (or fall below) certain thresholds. In a next step of refinement of the model, authorities will still define thresholds, but will not take all possible measures themselves, but charge the farmers with taxes when they exceed the fertiliser discharge limit. Farmers will then be endowed with rules which tell them whether it is better for them to pay the taxes or take appropriate measures against eutrophication themselves. The rationale of our paper is to show how stepwise refinement of a model can contribute to our understanding of the interactions between water resource decision makers of different levels and the natural environment. It is part of our efforts to develop agent-based models for application to issues of water treatment - as is done in the FIRMA project