Artificial Intelligence
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in expert systems: theory and algorithms
Probabilistic reasoning in expert systems: theory and algorithms
A note on the inevitability of maximum entropy
International Journal of Approximate Reasoning
Uncertain Information Processing in Expert Systems
Uncertain Information Processing in Expert Systems
A method of computing generalized Bayesian probability values for expert systems
IJCAI'83 Proceedings of the Eighth international joint conference on Artificial intelligence - Volume 1
A Symbolic Approach To Uncertainty Management
Applied Intelligence
Qualitative reasoning under ignorance and information-relevant extraction
Knowledge and Information Systems
Deduction with uncertain conditionals
Information Sciences—Informatics and Computer Science: An International Journal
Probalilistic Logic Programming under Maximum Entropy
ECSQARU '95 Proceedings of the European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty
States of matter, information organization and dimensions of expressiveness
Proceedings of the 1st conference on Computing frontiers
Combining probabilistic logic programming with the power of maximum entropy
Artificial Intelligence - Special issue on nonmonotonic reasoning
Infodynamics: Analogical analysis of states of matter and information
Information Sciences: an International Journal
Knowledge processing under information fidelity
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Constraints as data: a new perspective on inferring probabilities
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Measuring inconsistency in probabilistic knowledge bases
UAI '09 Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence
Relational probabilistic conditional reasoning at maximum entropy
ECSQARU'11 Proceedings of the 11th European conference on Symbolic and quantitative approaches to reasoning with uncertainty
Credal networks under maximum entropy
UAI'00 Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence
Automated reasoning for relational probabilistic knowledge representation
IJCAR'10 Proceedings of the 5th international conference on Automated Reasoning
Reflections on logic and probability in the context of conditionals
WCII'02 Proceedings of the 2002 international conference on Conditionals, Information, and Inference
SUM'12 Proceedings of the 6th international conference on Scalable Uncertainty Management
Transactions on Large-Scale Data- and Knowledge-Centered Systems VI
Inconsistency measures for probabilistic logics
Artificial Intelligence
| Hi-index | 0.00 |
SPIRIT is an expert system shell for probabilistic knowledge bases. Knowledge acquisition is performed by processing facts and rules on discrete variables in a rich syntax. The shell generates a probability distribution which respects all acquired facts and rules and which maximizes entropy. The user-friendly devices of SPIRIT to define variables, formulate rules and create the knowledge base are revealed in detail. Inductive learning is possible. Medium sized applications show the power of the system.