Combining dependent evidential bodies that share common knowledge
DOI10.1016/j.ijar.2014.05.010zbMath1433.60082OpenAlexW2037995185MaRDI QIDQ465610
Takéhiko Nakama, Enrique H. Ruspini
Publication date: 23 October 2014
Published in: International Journal of Approximate Reasoning (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.ijar.2014.05.010
probability theoryconditional independencetransferable belief modeltheory of evidenceDempster-Shafer formuladependent evidential body
Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20) Knowledge representation (68T30)
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Cites Work
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- Idempotent conjunctive combination of belief functions: extending the minimum rule of possibility theory
- Belief functions combination without the assumption of independence of the information sources
- Reinvestigating Dempster's idea on evidence combination
- Two views of belief: Belief as generalized probability and belief as evidence
- Fuzzy set connectives as combinations of belief structures
- The hierarchical hidden Markov model: Analysis and applications
- Belief functions: The disjunctive rule of combination and the generalized Bayesian theorem
- The transferable belief model
- On the justification of Dempster's rule of combination
- Conjunctive and disjunctive combination of belief functions induced by nondistinct bodies of evidence
- A User's Guide to Measure Theoretic Probability
- On the unicity of dempster rule of combination
- Equation of State Calculations by Fast Computing Machines
- Error bounds for convolutional codes and an asymptotically optimum decoding algorithm
- Upper and Lower Probabilities Induced by a Multivalued Mapping
- Monte Carlo sampling methods using Markov chains and their applications
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