On Understanding Catastrophe — The Case of Highly Severe Influenza-Like Illness

Computational epidemiology is a form of spatiotemporal reasoning in which social link structures are employed, and spatially explicit models are specified and executed. We point to issues thus far addressed neither by engineers, nor scientists, in the light of a use case focusing on catastrophic scenarios that assume the emergence of a highly unlikely but lethal and contagious strain of influenza. Our conclusion is that important perspectives are missing when dealing with policy issues resulting from scenario execution and analyses in computational epidemiology

Implementing an Agent Trade Server

An experimental server for stock trading autonomous agents is presented and made available, together with an agent shell for swift development. The server, written in Java, was implemented as proof-of-concept for an agent trade server for a real financial exchange.Comment: 14 pages, 7 figures, intended for B/W printin

The Blogosphere at a Glance — Content-Based Structures Made Simple

A network representation based on a basic wordoverlap similarity measure between blogs is introduced. The simplicity of the representation renders it computationally tractable, transparent and insensitive to representation-dependent artifacts. Using Swedish blog data, we demonstrate that the representation, in spite of its simplicity, manages to capture important structural properties of the content in the blogosphere. First, blogs that treat similar subjects are organized in distinct network clusters. Second, the network is hierarchically organized as clusters in turn form higher-order clusters: a compound structure reminiscent of a blog taxonomy

Algebras for Agent Norm-Regulation

An abstract architecture for idealized multi-agent systems whose behaviour is regulated by normative systems is developed and discussed. Agent choices are determined partially by the preference ordering of possible states and partially by normative considerations: The agent chooses that act which leads to the best outcome of all permissible actions. If an action is non-permissible depends on if the result of performing that action leads to a state satisfying a condition which is forbidden, according to the norms regulating the multi-agent system. This idea is formalized by defining set-theoretic predicates characterizing multi-agent systems. The definition of the predicate uses decision theory, the Kanger-Lindahl theory of normative positions, and an algebraic representation of normative systems.Comment: 25 page

Modeling Epidemic Spread in Synthetic Populations - Virtual Plagues in Massively Multiplayer Online Games

A virtual plague is a process in which a behavior-affecting property spreads among characters in a Massively Multiplayer Online Game (MMOG). The MMOG individuals constitute a synthetic population, and the game can be seen as a form of interactive executable model for studying disease spread, albeit of a very special kind. To a game developer maintaining an MMOG, recognizing, monitoring, and ultimately controlling a virtual plague is important, regardless of how it was initiated. The prospect of using tools, methods and theory from the field of epidemiology to do this seems natural and appealing. We will address the feasibility of such a prospect, first by considering some basic measures used in epidemiology, then by pointing out the differences between real world epidemics and virtual plagues. We also suggest directions for MMOG developer control through epidemiological modeling. Our aim is understanding the properties of virtual plagues, rather than trying to eliminate them or mitigate their effects, as would be in the case of real infectious disease.Comment: Accepted for presentation at Digital Games Research Association (DiGRA) conference in Tokyo in September 2007. All comments to the authors (mail addresses are in the paper) are welcom

Parrondo Strategies for Artificial Traders

On markets with receding prices, artificial noise traders may consider alternatives to buy-and-hold. By simulating variations of the Parrondo strategy, using real data from the Swedish stock market, we produce first indications of a buy-low-sell-random Parrondo variation outperforming buy-and-hold. Subject to our assumptions, buy-low-sell-random also outperforms the traditional value and trend investor strategies. We measure the success of the Parrondo variations not only through their performance compared to other kinds of strategies, but also relative to varying levels of perfect information, received through messages within a multi-agent system of artificial traders.Comment: 10 pages, 4 figure