Foundations of logic programming
Foundations of logic programming
Artificial Intelligence
An introduction to mathematical logic and type theory: to truth through proof
An introduction to mathematical logic and type theory: to truth through proof
An analysis of first-order logics of probability
Artificial Intelligence
Type theory and functional programming
Type theory and functional programming
Probabilistic logic programming
Information and Computation
Reasoning about knowledge and probability
Journal of the ACM (JACM)
Handbook of logic in artificial intelligence and logic programming
Stochastic lambda calculus and monads of probability distributions
POPL '02 Proceedings of the 29th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Modeling Uncertainty in Deductive Databases
DEXA '94 Proceedings of the 5th International Conference on Database and Expert Systems Applications
Higher-order unification and matching
Handbook of automated reasoning
Logic and Learning
Reasoning about Uncertainty
ACM SIGKDD Explorations Newsletter
Models for machine learning and data mining in functional programming
Journal of Functional Programming
A probabilistic language based upon sampling functions
Proceedings of the 32nd ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Personalisation for user agents
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Machine Learning
FUNCTIONAL PEARLS: Probabilistic functional programming in Haskell
Journal of Functional Programming
Lifted first-order probabilistic inference
Lifted first-order probabilistic inference
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
PRISM: a language for symbolic-statistical modeling
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
First-order probabilistic inference
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Lifted first-order probabilistic inference
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
BLOG: probabilistic models with unknown objects
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
An architecture for rational agents
DALT'05 Proceedings of the Third international conference on Declarative Agent Languages and Technologies
Combining bayesian networks with higher-order data representations
IDA'05 Proceedings of the 6th international conference on Advances in Intelligent Data Analysis
Factor graphs and the sum-product algorithm
IEEE Transactions on Information Theory
Interactive Rough-Granular Computing in Pattern Recognition
PReMI '09 Proceedings of the 3rd International Conference on Pattern Recognition and Machine Intelligence
Approximation Spaces in Rough-Granular Computing
Fundamenta Informaticae - Understanding Computers' Intelligence Celebrating the 100th Volume of Fundamenta Informaticae in Honour of Helena Rasiowa
Declarative programming for agent applications
Autonomous Agents and Multi-Agent Systems
ILP'10 Proceedings of the 20th international conference on Inductive logic programming
Modeling rough granular computing based on approximation spaces
Information Sciences: an International Journal
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This paper provides a study of probabilistic modelling, inference and learning in a logic-based setting. We show how probability densities, being functions, can be represented and reasoned with naturally and directly in higher-order logic, an expressive formalism not unlike the (informal) everyday language of mathematics. We give efficient inference algorithms and illustrate the general approach with a diverse collection of applications. Some learning issues are also considered.