Catálogo de publicaciones - libros

A new approach is suggested under the slogan “Keep it Descriptive Stupid” (KIDS) that encapsulates a trend in increasingly descriptive agent-based social simulation. The KIDS approach entails one starts with the simulation model that relates to the target phenomena in the most straight-forward way possible, taking into account the widest possible range of evidence, including anecdotal accounts and expert opinion. Simplification is only applied if and when the model and evidence justify this. This contrasts sharply with the KISS approach where one starts with the simplest possible model and only moves to a more complex one if forced to. An example multi-agent simulation of domestic water demand and social influence is described.

In this paper, we examined the conditions under which evolutionary algorithms (EAs) are appropriate for artificial market models. We constructed three types of agents, which are different in efficiency and accuracy of learning. They were compared using acquired payoff in a minority game, a simplified model of a financial market. As a result, when the dynamics of the financial price was complex to some degree, an EA-like learning type was appropriate for the modeling of financial markets.

This paper focuses on how simulation results are to agent modeling in multiagent-based simulation (MABS) and investigates such sensitivity by comparing results where agents have different , , Q-learning and Sarsa, in the context of reinforcement learning. Through an analysis of simulation results in a bargaining game as one of the canonical examples in game theory, the following implications have been revealed: (1) even a slight difference has an essential influence on simulation results; (2) testing in static and dynamic environments highlights the different tendency of results; and (3) three stages in both Q-learning and Sarsa agents (, (a) competition; (b) cooperation; and (c) learning impossible) are found in the dynamic environment, while no stage is found in the static environment. From these three implications, the following very guidelines for modeling agents can be derived: (1) cross-element validation for specifying key factors that affect simulation results; (2) a comparison of results between the static and dynamic environments for determining candidates to be investigated in detail; and (3) sensitive analysis for specifying applicable range for learning agents.

Recent events have highlighted the importance of good models of crowds, however many existing crowd models are either computationally inefficient, or are missing a crucial human behaviour in crowds: local pushing. After discussing some essential aspects of force in crowds, and considering some existing models, we propose an efficient agent-based model of crowd evacuation that incorporates pushing forces and injuries. Basing our model on existing work, we extend this model to investigate force effects at different crowd densities. Analysis of our model shows significant effects of force on the crowd, as well as significant effects of crowd density when measuring the number of agents still trapped inside the space after a fixed time.

In this research, we propose some group dynamics that promote cooperative behavior in systems with social dilemmas and hence enhances their performance. If cooperative behavior among self-interest individuals is established, effective distribution of resources and useful allocation of tasks based on coalition formation can be realized. In order to realize these group dynamics, we extend the partner choice mechanisms for 2-IPD to that for N-person Dilemma game. Furthermore, we propose group split based on metanorm as a new group dynamic. A series of evolutionary simulations confirm that this group dynamic: i) establishes and maintains cooperation, and ii) enhances the performance of the systems consisting of self-interest players in Social Dilemmas situations.

In this paper, an innovative application of scheduling methodology is advocated for the emerging service, which is named “social coordination” in the ubiquitous information environments. A typical service expected in ubiquitous computing is information provision adapted to each user’s current situation. The service is supposed to increase a single person’s convenience. However, a new type of service (“social coordination”) is also possible for improving conveniences of the people sharing the ubiquitous information environment. The author explains the concept of “ubiquitous scheduling” that eludes congestions in the society by scheduling people’s activities efficiently and rationally. To evaluate effectiveness of the concept, a multi-agent scheduler for an amusement park problem is implemented, which coordinates the demands for rides by tens of thousands people and makes suggestions as to when they should visit attractions in the amusement park to avoid standing in long lines.

Anthropologists have yet to adequately investigate the evolution of food sharing despite its prevalence among contemporary human societies. As an initial step toward rectifying this lapse, I present preliminary population-genetic results generated by an agent-based model of Plio/Pleistocene hominid food sharing. SHARE explores the dynamics of a unique conceptual model that treats fragmented closed habitat patches as the loci of hominid social evolution and investigates the altruistic behavior of food sharing using multilevel selection theory. Data collected from artificial societies of hominid foragers demonstrate that specific levels of ecological patchiness facilitate the evolution of food sharing due to the fitness benefits bestowed upon subsistence–related trait groups.

An incursion management model was developed to estimate the regional economy effects of a potential exotic pest or disease incursion in the agricultural sector. By developing an agent based spatial model that integrates the biophysical aspects of the disease incursion with the agricultural production system and the wider regional economy the model can be used to analyze the effectiveness and economic implications of alternative management strategies for a range of different incursion scenarios. A case study application of the model investigates the impact of a potential incursion of Karnal bunt in wheat in a valuable agricultural producing region of Australia.

A simulation-based tool is described which will be used to investigate how the actors in a transport chain are expected to act when different types of governmental control policies are applied, such as, fuel taxes, road tolls, vehicle taxes and requirements on vehicles. The simulator is composed of two layers, one layer simulating the physical activities taking place in the transport chain, e.g., production, storage, and transports of goods, and another layer simulating the different actors’ decision making processes. The decision layer is implemented by a multi-agent system where each agent corresponds to a particular actor and models the way it acts in different situations. The simulator will be used for analyzing the costs and environmental effects, and will in this way provide guidance in decision making regarding control policies. In addition, it will be possible for companies to use the simulator in order to determine cost-effective strategies given different (future) scenarios.

Some types of animals exploit patterns created in the environment as external mental states, thus obtaining an extension of their mind. In the case of social animals the creation and exploitation of such patterns can be shared, which supports a form of shared extended mind or collective intelligence. This paper explores this shared extended mind principle for social animals in more detail. Its main goal is to analyse and formalise the dynamic properties of the processes involved, both at the local level (the basic mechanisms) and the global level (the emerging properties of the whole), and their relationships. A case study in social ant behaviour in which shared extended mind plays an important role is used as illustration. For this case simulations are described based on specifications of local properties, and global properties are specified and verified.