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In this paper, we detail some technical alternatives when building a coherent distributed visual sensor network by using the multi-agent paradigm. We argue that the multi-agent paradigm fits well within the visual sensor network architecture and in this paper we specially focus on the problem of distributed data fusion. Three different data fusion coordination schemes are proposed and experimental...
New methods for team optimal decision, based on a stochastic agent coordination, are presented, implemented and tested. The methods are extensions of the cross-entropy algorithm (CE), initially dedicated to rare-event simulation. In particular, this paper investigates how the contributions of the agents could be involved in the simulation process. The approaches are tested on a SD-assignment problem,...
This paper presents the proactive logistics toolkit (PROLOG), a collaborative agent system and logistics network simulator that allows users to coordinate the transfer of supplies across a dynamically changing logistics network in a fully distributed, netcentric way. A collection of cognitive agents and asset classes models the logistics network: clients, their supply inventories, vehicles, and transportation...
This article focuses on the use of multi-agent systems for modelling of micro-unmanned aerial vehicles (MAVs) in a distributed control task. The task regards a search and destroy scenario in the context of security and urban counter-terrorism. In the simulations developed, a swarm composed of four autonomous flying robots, driven by an embodied neural network controller, has to approach a target deployed...
Effective communication among agents in large teams is crucial because the members share a common goal but only have a partial views of the environment. Information sharing is difficult in a large team because, a team member may have a piece of valuable information but not know who needs the information, since it is infeasible to know what each other agent is doing. Although much related work has...
This paper introduces a framework for regression with dimensionally distributed data with a fusion center. A cooperative learning algorithm, the iterative conditional expectation algorithm (ICEA), is designed within this framework. The algorithm can effectively discover linear combinations of individual estimators trained by each agent without transferring and storing large amount of data amongst...
Maintenance of air tracks requires regular track updates to counter effects of aging. In multi-sensor networks, sensors need to cooperate to optimise the time allocation for track maintenance. Early updates lead to waste of time without improving the track quality, while late updates may result in track drop as the target has moved out of sight of the updating sensor. Earlier research has presented...
A formal approach to the design of situation analysis and decision support systems is justified and unavoidable if one is interested in reproducibility/traceability of results, satisfaction of constraints, and a language to represent and reason about dynamic situations. In this paper, we propose the integration of two multiagent modeling paradigms, abstract state machines and interpreted systems,...
Previous work in automating insider threat detection has included top-down analysis and fusion of events from network and system monitors. Situation-awareness can extend the capability of such techniques to include observables outside of cyber-space. The application of situation-management to insider threats is becoming more practical due to the growing volume of different types of transactions and...
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