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Today's service-oriented systems realize many ideas from the research conducted a decade or so ago in multiagent systems. Because these two fields are so deeply connected, further advances in multiagent systems could feed into tomorrow's successful service-oriented computing approaches.This article describes a 15-year roadmap for service-oriented multiagent(More)
The paper describes a new approach toward the study of anticipatory behavior in adaptive learning systems, an approach based on electrophysiological evidence of anticipatory behavior of the human brain. The basic idea is to study brain potentials related to anticipation of some event. Here we describe our work with the CNV anticipatory potential. We(More)
1.1. The social dynamics of language change Language change is a historical process rooted in synchronic social dynamics. In countless communicative interactions between individuals, novel linguistic variants can emerge, diffuse widely, become integrated into the grammar of the speech community and be transmitted to future generations. When the time course(More)
Previous work in knowledge transfer in machine learning has been restricted to tasks in a single domain. However , evidence from psychology and neuroscience suggests that humans are capable of transferring knowledge across domains. We present here a novel learning method, based on neuroevolution, for transferring knowledge across domains. We use(More)
We simulate the dynamics of diffusion and establishment of norms, variants adopted by the majority of agents, in a large social influence network with scale-free small-world properties. Diffusion is modeled as the probabilistic uptake of one of several competing variants by agents of unequal social standing. We find that novel variants diffuse following an(More)
Sociological models of human behavior can explain population-level phenomena within social systems; computer modeling can simulate a wide variety of scenarios and allow one to pose and test hypotheses about the social system. In this paper, we model and examine the spread of information through personal conversations in a simulated socio-technical network(More)
Eliminating interactions among individuals is an important means of blocking contagion spread, e.g., closing schools during an epidemic or shutting down electronic communication channels during social unrest. We study contagion blocking in networked populations by identifying edges to remove from a network, thus blocking contagion transmission pathways. We(More)
In this paper we describe a multiagent simulation model of human behavior in the aftermath of a hypothetical, large-scale, human-initiated crisis in the center of Washington D.C. Prior studies of this scenario have focused on modeling the physical effects of the attack, such as thermal and blast effects , prompt radiation, and fallout. Casualty and(More)
We describe InterSim, a general purpose flexible framework for simulating graph dynamical systems (GDS) and their generalizations. GDS provide a powerful formalism to model and analyze agent-based systems (ABS) because there is a direct mapping between nodes and edges (which denote interactions) in a GDS and agents and interactions in an ABS, thereby(More)