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Deductive belief change
In a 2003-article, Sven Ove Hansson discusses the justificatory structure of a belief base, by highlighting that some beliefs of the belief base are...
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Semantics of Belief Change Operators for Intelligent Agents
This paper summarises several contributions to the theory of belief change by the authors’ dissertation thesis. First, a relational characterization...
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Reports, Observations, and Belief Change
We consider belief change in a context where information comes from reports, and the reporting agents may not be honest. In order to capture this...
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Hyperintensional Models and Belief Change
Formal frameworks for Epistemology need to have enough logical structure to enable interesting conclusions regarding epistemic phenomena and to be...
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A knowledge compilation perspective on queries and transformations for belief tracking
Nondeterministic planning is the process of computing plans or policies of actions achieving given goals, when there is nondeterministic uncertainty...
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Belief Reconfiguration
We study a generalisation of iterated belief revision in a setting where we keep track not only of the received information (in the form of messages)...
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Theory-relational belief revision
The prominent formal framework for belief change established by Alchourrón, Gärdenfors and Makinson circumscribes the territory of all rational...
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Belief space-guided approach to self-adaptive particle swarm optimization
Particle swarm optimization (PSO) performance is sensitive to the control parameter values used, but tuning of control parameters for the problem at...
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Integrating Evolutionary Prejudices in Belief Function Theory
This paper deals with belief change in the framework of Dempster-Shafer theory in the context where an agent has a prejudice, i.e., a priori...
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Belief entropy rate: a method to measure the uncertainty of interval-valued stochastic processes
Entropy rate, as an effective tool in information theory, can measure the uncertainty of stochastic processes modeled by probability mass function....
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A new interval constructed belief rule base with rule reliability
The combination rule explosion problem of belief rule base (BRB) is a difficult problem to solve in complex systems and has attracted wide attention....
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Hubs of belief networks across sociodemographic and ideological groups
Beliefs are essential components of the human mind, as they define personal identity, integration and adaptation to social groups. Most theoretical...
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Automated classification of Alzheimer's disease based on deep belief neural networks
When it comes to the causes of dementia, Alzheimer's disease is the most mysterious. There is no central genetic component connected to Alzheimer's...
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KFDBN: Kernelized Finetuned Deep Belief Network for recommendation
In today’s technologically evolved world, users have become accustomed to personalized tools that provide accurate and precise recommendations that...
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An online intrusion detection method for industrial control systems based on extended belief rule base
Intrusion detection in industrial control systems (ICS) is crucial for maintaining the security of physical information systems. However, the...
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An effective conflict management method based on belief similarity measure and entropy for multi-sensor data fusion
Multi-sensor data fusion has received substantial attention thanks to its ability to integrate information from distinct sources efficiently....
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A novel belief Tanimoto coefficient with its applications in multisource information fusion
Dempster-Shafer evidence theory (DST) is a versatile framework for handling uncertainty and provides a reliable method for data fusion. Managing...
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Toward fast belief propagation for distributed constraint optimization problems via heuristic search
Belief propagation (BP) approaches, such as Max-sum and its variants, are important methods to solve large-scale Distributed Constraint Optimization...
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A belief Rényi divergence for multi-source information fusion and its application in pattern recognition
Multi-source information fusion technology has been widely used because it can maximize the use of information that collected from multiple data...
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A novel approach for detection of APT malware using multi-dimensional hybrid Bayesian belief network
Due to the continuous evolution of adversary tactics, strategies, and processes, the contemporary digital universe is confronted with new obstacles...
