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In this paper we analyse the roosting effect among artificial vampires as a way to preserve altruism from cheaters exploitation. We simulate the formation and maintenance of new social structures (roosts) from initial populations as a consequence of both demographic growth and social organisation. Food-sharing among vampire bats (Desmodus Rotundus) is a well-known form of altruism, necessary for the survival of this species, supported by wide ethological evidence. By means of simulation, we study the performance of the system under varying mutation rate (giving rise to cheaters that exploit the altruistic mechanism) and roost size. Results show that the roosting effect can cope with sensible mutation levels. Moreover, the most robust size of roosts indicated by our simulations is shown to be comparable with the size actually found in nature. [ABSTRACT FROM AUTHOR]

Development of category structure in communication is studied by a constructive approach. Individuals having a word relation matrix as their internal structure communicate by uttering and accepting sentences. Words in sentences uttered are situated in relation with other words by each individual. Words make clusters according to their interrelationships. The structures and dynamics of clusters are studied. Coexisting commonality and individuality of clustering structure is observed in an ensemble of individuals. [ABSTRACT FROM AUTHOR]

Multi-agent methodology is used for various purposes, such as distributed solving problem, network management, etc. Multi-agent systems are also used for simulation. Usually, the emergence of macroscopic properties is studied by simulating the behavior of agents and their interactions at a microscopic level. It is a bottom-up approach. Recently emphasis has been placed on the links between the macroscopic and the microscopic levels combining the bottom-up and top down directions. We are currently developing a multi-agent simulator to illustrate and discuss the principles of the economic theory of renewable resource management. The management of renewable resources, from an economic point of view, may be based on public interventions at the macroscopic level or on regulation at the microscopic level. The simulator uses the Cormas environment [Bousquet et al., submitted]. First, a renewable resource dynamics is simulated on a theoretical grid. Second, economic agents are represented. Different agents, belonging to different stages of an industry, are represented. Agents collect the resources and others use this resource as an input for transformation. The agents' behavior and objectives are heterogeneous. Economic exchanges are simulated. We reproduce the market-oriented approach [Cheng & Wellman, 1996] which assumes that a general equilibrium sets a global price. We also simulate the trade rules proposed by Epstein and Axtell (1996) in which there is no global price. The aim is to evaluate the differences between these two approaches from the ecological and economic points of view. Third, when an industry is established we simulate various actions at the macroscopic level. Economic theory proposes various interventions such as taxes, quotas, trade and market organization. We test these actions and observe their effects on the society of agents. We observe the quantity of resources, the benefits to the agents, the rent obtained from the macroscopic interventions and how it is shared. This simulator provides a didactic framework to explain economic theory for resource management. Later, we will use it for field study by importing field data. From the computer science point of view, this simulator will be used to test various algorithms for agent coordination. From an economic point of view, it introduces the notion of space and a time frame in the scope of resource management. [ABSTRACT FROM AUTHOR]

Sim-ACTS is an agent-based computer simulation model of some aspects of ACTS theory [5]. It is the first of a series of models in which increasingly more aspects of ACTS theory will be encompassed. Sim-ACTS studies the effects of communication and organizational structure on organizational problem solving. It is a follow-up study of the TASSCS research project [15],[16]. The simulation experiments from the TASSCS project are replicated using the Sim-ACTS model.The article compares the results of TASSCS' simulations with those of the Sim-ACTS experiments. Sim-ACTS is implemented in SOAR [8], the implementation of a general cognitive theory [11]. [ABSTRACT FROM AUTHOR]

Multi-agent simulations aim at representing the dynamics of complex systems as resulting from multiple interactions between autonomous entities encapsulating their own perception of local environment. From our point of view, this approach would also require to take into account individualized perception of time. In this paper, we propose a new way to implement time distribution in multi-agent systems by associating to each agent its own time and rhythm to achieve its own actions. Our synthetic examples are extracted from our specific research project, dealing with a simulator of irrigated systems, where the parallelism of physical processes appears to be an important component of reality. Keywords: multi-agent simulation, time-representation [ABSTRACT FROM AUTHOR]

In this paper, we present some of our ongoing experimental research towards investigating advantages of modeling other agents in multiagent environments. We attempt to quantify the value or utility of building models about other agents using no more than the observation of others' behavior. We are interested in empirically showing that a modeler agent can take advantage of building and updating its beliefs about other agents. This advantage can make it perform better than an agent without modeling capabilities. We have been conducting a simulataion-based study using a competitive game called Meeting Scheduling Game as a testbed. First, we briefly describe our multiagent simultaion testbed. Then, we describe in detail our experimental study. We explore a range of strategies from least- to most-informed, and present some of our preliminary results on the relative performance of these strategies. Decreasing the a priori knowledge about the others and increasing the modeling capabilities we are able to define a series of "modeler" agents. Finally, we present a method for using probabilistic models about the others in such a way that the expected utility is maximized. [ABSTRACT FROM AUTHOR]

Current multi-agent simulations, which have many individual entities evolve and interact, often lead to the emergence of local groups of entities, but provide no means of manipulating them. To our mind, giving full a sense to multi-agent simulations would consist though in making use of such dynamically created potential groups, by granting them an existence of their own, and specific behaviours. Brought into operation, they would provide effective and new tools for modelling purposes : for instance, encapsulating physical laws which depend on scaling, thus giving means of apprehending micro-macro links in multi-agent simulations, or introducing the experimentater's viewpoints on the specific behaviours of such groups. We thus have to imagine how to give any set of agents means of becoming aware of their mutual interaction, and giving birth to new types of agents out of their collective activity. In other words we look for a computer equivalent to our own emergence recognition ability. We present here a conceptual reflexion on such matters in the light of our own experience in the development of the RIVAGE project at Orstom, which aims at simulating runoff and infiltration processes. Conversely, we believe that the development of our methods in such a novel and original field of research as the multi-agent simulation of pure physical processes will provide new ideas and tools useful for many multi-agent architectures and modelling purposes. Keywords: multi-agent simulations, multiple level of abstractions and scales, emergent phenomena, micro-macro link. [ABSTRACT FROM AUTHOR]

With the growing interest in Multi-Agent Systems (MAS's), the need of useful tools to design and make such systems evolve has become an important domain of research. In this context, on the one hand, we are interested in modeling the organization of a MAS and on the other hand, in adapting this organization to environmental changes during the execution of the system. In our sense, the organization has to deal with the structure of the system according to the definition and the allocation of responsibilities regarding execution of tasks among agents. In this paper, we present our organizational model whose core notions are roles and links. By combining this organizational model with the dependence theory, we explore a way that allows the detection of inconsistencies in the organization of a MAS. [ABSTRACT FROM AUTHOR]

An on-going project investigating group formation, stereotyping and cultural evolution using an artificial society is outlined. Agents culturally interact by exchanging behavioural rules and cultural markers. They economically interact by playing games of the Prisoners Dilemma. The mode of game play is novel because agents apply stochastic repeated game strategies not to individuals but to subjectively stereotyped groups (based on cultural makers). Agents consequently treat stereotyped groups as single players with whom they are involved in an on-going game of iterated PD. It is envisaged that such cultural processes may display a form of "second order emergence" [11] in which agents come to recognise the cultural groupings that have emerged within the society. Some initial experimental results are presented with tentative observations. [ABSTRACT FROM AUTHOR]

The issue as to whether computer simulation can be considered a valid tool for improving the predictive capacity of social scientific theories is still controversial (e.g., Troitzsch 1997 and Scott et al. 1997, seem to deny it). Instead, the role of computer simulation for testing models and experimenting on social phenomena is denied by no-one in the field (see Halpin 1997). [ABSTRACT FROM AUTHOR]

The hypothesis is that the exchanges of goods structure the society, and especially the non-merchant exchanges. Their aim is to express unselfishness, but also to generate a moral debt that builds strong reciprocal links. A multi-agent system was built with 100 agents and a resource, the interactions being only gifts. For the simulations, the agents have different rules to perform gifts and to organize their memory. The results are analyzed by the agent as well as by the modeller, with different points of view: either local or global and with different time length. [ABSTRACT FROM AUTHOR]

Honey bee colonies consist of tens of thousands of interacting bees. The colony has only limited centralised control and many of its functions arise from the self-organised actions of individual bees. We use an example from nectar foraging to illustrate how process algebras may be used to describe formally the behaviour of bees as communicating agents. Logical properties of a ‘colony' of these agents are then established and a computer simulation is described which adds dynamics to the process algebra description. [ABSTRACT FROM AUTHOR]

This paper concerns agent based experiments in the field of negotiation and exchange simulation. A computer simulation environment is built, showing the emergence of chaotic price sequences in a simple model of interacting consumers and vendors, both equipped with minimal rules. "Swarm" is the framework of the model (www.santafe.edu/projects/swarm), a simulation tool with a strong object oriented structure, also very useful to separate in a clear way the model level from the level of the observer. Swarm if fully programmable in Objective C, with many powerful libraries, aimed at modeling the objects and the schedules of our experiments, with lists and arrays where necessary. Finally we introduce a tool (Cross Target method: CT), useful in building artificial laboratories, for experiments with learning, self-developed consistency and interaction of agents in artificial worlds, in order to observe the emergence of complexity without a priori behavioral rules: The perspective of our work is that of developing CT within the Swarm framework to replicate the ABCDE experiment in this light-rules or no-rules context. [ABSTRACT FROM AUTHOR]

In many domains, agent-based system modeling competes with equation-based approaches that identify system variables and evaluate or integrate sets of equations relating these variables. The distinction has been of great interest in a project that applies agent-based modeling to industrial supply networks, since virtually all computer-based modeling of such networks up to this point has used system dynamics, an approach based on ordinary differential equations (ODE's). This paper summarizes the domain of supply networks and illustrates how they can be modeled both with agents and with equations. It summarizes the similarities and differences of these two classes of models, and develops criteria for selecting one or the other approach. [ABSTRACT FROM AUTHOR]

Theories in the social sciences are informed either by sociology or by economics. That is, they either draw generalizations from verbal descriptions of social inter action or from mathematical representations of interacting agents as constrained maximizers. The three models discussed in this paper are not less rigorous than economic models and, because they are validated relative to a formal logic rather than mathematics alone, capture much more of the richness of sociological anal ysis than does the economics approach. Moreover, each has, in its own way, been developed to capture salient characteristics of observed regularities in specific social interactions. Together they exemplify a set of modelling techniques and an integrated methodology which capture the rigour and precision of the econo mist's approach to the social sciences while, at the same time, capturing the sug gestiveness and richness of the sociologist's approach. [ABSTRACT FROM AUTHOR]

When the micro-units of emerging dynamic processes are cognitive agents, a very important and unique phenomenon arises, called Cognitive Emergence (CE). We argue that: CE characterises the theory of Sociological dynamics with respect to other forms of emergence at different level of organisation (ex. physics, biology, etc.); CE has a very strong influence on the process of emergence, changing it, and should be taken into account in simulating and modelling social phenomena; certain important emerging social phenomena, like social norms cannot be explained at all without CE; CE has critical consequences on the process of "immergence" i.e. the process through which the macro-level emerging structure or global result ‘feedbacks' into the micro-level re-shaping the "elementary" behaviours. We examine the case of dependence relationships. [ABSTRACT FROM AUTHOR]

The goal of this introduction is to point out several similarities and differences between the research fields of multi-agent systems and social simulation. We show that these fields are complementary in several aspects, thus each one can benefit from results that emerge from the other. We finish the introduction by presenting and classifying the contributions in this volume. [ABSTRACT FROM AUTHOR]

It is generally acknowledged that norms and normative action emphasize autonomy on the side of decision. But what about the autonomous formation of normative goals? This paper is intended to contribute to a theory of how agents form normative beliefs and goals, and to formulate general but non exhaustive principles of norm based autonomous agent-hood - namely goal generation and decision making-upon which to construct software agents. [ABSTRACT FROM AUTHOR]

In this paper, we present some preliminary results concerning the extension of dependence theory [2] and social reasoning [9] to cope with the notion of organizational roles. In order to accomplish this task, we first present a rather informal definition of organization and roles, showing how this additional dimension can be represented within a 3-layered architecture of mental states. We then restrict our analysis to the domain level, by extending our original notions of unilateral and bilateral dependence, as well as that of goal situation, to show that just by representing explicitly the input source of some mental attitudes one can easily explain some interesting social phenomena, like agents' adequacy to roles and vice-versa. For methodological reasons, we divide this analysis along two main axes, i.e., the inter-agent and the intra-agent dimensions. [ABSTRACT FROM AUTHOR]