An overview of algorithmic approaches to compute optimum entropy distributions in the expert system shell MECore (extended version)

DOI10.1016/j.jal.2016.05.003zbMath1436.68341OpenAlexW2370746213MaRDI QIDQ507545

David Marenke, Engelbert Mittermeier, Nico Potyka

Publication date: 6 February 2017

Published in: Journal of Applied Logic (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jal.2016.05.003

zbMATH Keywords

maximum entropyprobabilistic reasoninguncertain reasoningprobabilistic conditional logic

Mathematics Subject Classification ID

Probability distributions: general theory (60E05) Knowledge representation (68T30) Theory of languages and software systems (knowledge-based systems, expert systems, etc.) for artificial intelligence (68T35)

Uses Software

• L-BFGS
• SPIRIT

Cites Work

• An analysis of first-order logics of probability
• Combining probabilistic logic programming with the power of maximum entropy
• On the limited memory BFGS method for large scale optimization
• Probabilistic logic
• Boole's logic and probability. A critical exposition from the standpoint of contemporary algebra, logic and probability theory. 2nd ed., rev. and enlarged
• Probabilistic logic programming
• I-divergence geometry of probability distributions and minimization problems
• In defense of the maximum entropy inference process
• A geometric interpretation of Darroch and Ratcliff's generalized iterative scaling
• Towards classifying propositional probabilistic logics
• Markov logic networks
• Features of the Expert-System-Shell SPIRIT
• Markov Logic: An Interface Layer for Artificial Intelligence
• Column Generation Methods for Probabilistic Logic
• Using Histograms to Better Answer Queries to Probabilistic Logic Programs
• Probabilistic Inductive Logic Programming
• Generalized Iterative Scaling for Log-Linear Models
• Conditionals in nonmonotonic reasoning and belief revision. Considering conditionals as agents
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