Add to ORKGWe introduce a robust approach to diagnostic information fusion within a network of probabilistic models distributed throughout a system of agents. In particular, the approach combines results from local fusion processes in a consis-tent manner and it is applicable in a significant class of fusion problems. It supports sequential fusion of large amounts of heterogeneous information without centralized fusion control in distributed models which can frequently change at runtime
This paper discusses techniques for fusion in contemporary situation assessment applications. Such a...
The assessment of dynamic situations using data from multiple sensors occurs in many military and ci...
AbstractMultiply sectioned Bayesian networks for single-agent systems are extended into a framework ...
We introduce a robust approach to diagnostic information fusion within a network of probabilistic mo...
We introduce Distributed perception networks (DPNs), a distributed architecture for efficient and re...
This paper introduces a multi agent-based approach to fusion of heterogeneous data and information, ...
© IFAC. We present a Monte Carlo solution to the distributed data fusion problem and apply it to dis...
In complex multi-agent fusion systems resource conflicts are very likely to occur. We propose an alg...
This paper introduces an information theoretic approach to verification of causal models in modular ...
The paper evaluates a class of fusion systems that support interpretation of complex patterns consis...
Local Bayesian fusion approaches aim to reduce high storage and computational costs of Bayesian fusi...
We address the point of introducing fusion and representation techniques for distributed knowledge s...
We present a robust distributed algorithm for approximate probabilistic inference in dynamical syste...
Modern situation assessment and controlling applications often require efficient fusion of large am...
This paper describes a theory of data fusion in random-set formalism. Data fusion problems are defin...
This paper discusses techniques for fusion in contemporary situation assessment applications. Such a...
The assessment of dynamic situations using data from multiple sensors occurs in many military and ci...
AbstractMultiply sectioned Bayesian networks for single-agent systems are extended into a framework ...
We introduce a robust approach to diagnostic information fusion within a network of probabilistic mo...
We introduce Distributed perception networks (DPNs), a distributed architecture for efficient and re...
This paper introduces a multi agent-based approach to fusion of heterogeneous data and information, ...
© IFAC. We present a Monte Carlo solution to the distributed data fusion problem and apply it to dis...
In complex multi-agent fusion systems resource conflicts are very likely to occur. We propose an alg...
This paper introduces an information theoretic approach to verification of causal models in modular ...
The paper evaluates a class of fusion systems that support interpretation of complex patterns consis...
Local Bayesian fusion approaches aim to reduce high storage and computational costs of Bayesian fusi...
We address the point of introducing fusion and representation techniques for distributed knowledge s...
We present a robust distributed algorithm for approximate probabilistic inference in dynamical syste...
Modern situation assessment and controlling applications often require efficient fusion of large am...
This paper describes a theory of data fusion in random-set formalism. Data fusion problems are defin...
This paper discusses techniques for fusion in contemporary situation assessment applications. Such a...
The assessment of dynamic situations using data from multiple sensors occurs in many military and ci...
AbstractMultiply sectioned Bayesian networks for single-agent systems are extended into a framework ...