Agent-based simulation of animal behaviour

In this paper it is shown how animal behaviour can be simulated in an agent-based manner. Different models are shown for different types of behaviour, varying from purely reactive behaviour to pro-active, social and adaptive behaviour. The compositional development method for multi-agent systems DESIRE and its software environment supports the conceptual and detailed design, and execution of these models. Experiments reported in the literature on animal behaviour have been simulated for a number of agent models

A Computational Agent Model for Hebbian Learning of Social Interaction

In social interaction between two persons usually a person displays understanding of the other person. This may involve both nonverbal and verbal elements, such as bodily expressing a similar emotion and verbally expressing beliefs about the other person. Such social interaction relates to an underlying neural mechanism based on a mirror neuron system, as known within Social Neuroscience. This mechanism may show different variations over time. This paper addresses this adaptation over time. It presents a computational model capable of learning social responses, based on insights from Social Neuroscience. The presented model may provide a basis for virtual agents in the context of simulation-based training of psychotherapists, gaming, or virtual stories. © 2011 Springer-Verlag

A network-oriented adaptive agent model for learning regulation of a highly sensitive person’s response

Inspired by the work of Elaine Aron, in this paper a human-like adaptive computational agent model of the internal processes of a highly sensitive person (HSP) is presented. This agent model was used to get a better understanding of what goes wrong in these internal processes once this person gets upset. A scenario is addressed where a highly sensitive person will get upset by an external stimulus and will not be able to calm down by herself. Yet in a social context the interaction with a second person (without high sensitivity) will calm the HSP down, thus contributing to regulation. To obtain an adaptive model a Hebbian learning connection was integrated. During interaction with a second person this Hebbian learning link will become stronger, which makes it possible for a HSP to become independent after some time and be able to regulate upsetting external stimuli all by herself

Multiagent Cooperative Learning Strategies for Pursuit-Evasion Games

This study examines the pursuit-evasion problem for coordinating multiple robotic pursuers to locate and track a nonadversarial mobile evader in a dynamic environment. Two kinds of pursuit strategies are proposed, one for agents that cooperate with each other and the other for agents that operate independently. This work further employs the probabilistic theory to analyze the uncertain state information about the pursuers and the evaders and uses case-based reasoning to equip agents with memories and learning abilities. According to the concepts of assimilation and accommodation, both positive-angle and bevel-angle strategies are developed to assist agents in adapting to their environment effectively. The case study analysis uses the Recursive Porous Agent Simulation Toolkit (REPAST) to implement a multiagent system and demonstrates superior performance of the proposed approaches to the pursuit-evasion game

Microdynamics of Illegitimacy and Complex Urban Violence in Medellin, Colombia

For most of the past 25 years, Medellin, Colombia, has been an extreme case of complex, urban violence, involving not just drug cartels and state security forces, but also street gangs, urban guerrillas, community militias, paramilitaries, and other nonstate armed actors who have controlled micro-territories in the city's densely populated slums in ever-shifting alliances. Before 2002, Medellin's homicide rate was among the highest in the world, but after the guerrillas and militias were defeated in 2003, a major paramilitary alliance disarmed and a period of peace known as the "Medellin Miracle" began. Policy makers facing complex violence elsewhere were interested in finding out how that had happened so quickly. The research presented here is a case study of violence in Medellin over five periods since 1984 and at two levels of analysis: the city as a whole, and a sector called Caicedo La Sierra. The objectives were to describe and explain the patterns of violence, and determine whether legitimacy played any role, as the literature on social stability suggested it might. Multilevel, multidimensional frameworks for violence and legitimacy were developed to organize data collection and analysis. The study found that most decreases in violence at all levels of analysis were explained by increases in territorial control. Increases in collective (organized) violence resulted from a process of "illegitimation," in which an intolerably unpredictable living environment sparked internal opposition to local rulers and raised the costs of territorial control, increasing their vulnerability to rivals. As this violence weakened social order and the rule of law, interpersonal-communal (unorganized) violence increased. Over time, the "true believers" in armed political and social movements became marginalized or corrupted; most organized violence today is motivated by money. These findings imply that state actors, facing resurgent violence, can keep their tenuous control over the hillside slums (and other "ungoverned" areas) if they can avoid illegitimizing themselves. Their priority, therefore, should be to establish a tolerable, predictable daily living environment for local residents and businesses: other anti-violence programs will fail without strong, permanent, and respectful governance structures