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Gaining wide acceptance for the use of agents in industry requires both relating it to the nearest antecedent technology (object-oriented software development) and using artifacts to support the development environment throughout the full system lifecycle. We address both of these requirements using AUML, the Agent UML (Unified Modeling Language)—a set of(More)
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(More)
It is generally accepted that the environment is an essential compound of multiagent systems (MASs). Yet the environment is typically assigned limited responsibilities, or even neglected entirely, overlooking a rich potential for the paradigm of MASs. Opportunities that environments offer, have mostly been researched in the domain of situated MASs. However,(More)
Emergent self-organization in multi-agent systems appears to contradict the second law of thermodynamics. This paradox has been explained in terms of a coupling between the macro level that hosts self-organization (and an apparent reduction in entropy), and the micro level (where random processes greatly increase entropy). Metaphorically, the micro level(More)
The use of digital pheromones for controlling and coordinating swarms of unmanned vehicles is studied under various conditions to determine their effectiveness in multiple military scenarios. The study demonstrates the effectiveness of these pheromone algorithms for surveillance, target acquisition, and tracking. The algorithms were demonstrated on hardware(More)
Without an environment, an agent is effectively useless. Cut off from the rest of its world, the agent can neither sense nor act. An environment provides the conditions under which an entity (agent or object) can exist. It defines the properties of the world in which an agent will function. Designing effective agents requires careful consideration of both(More)