Probabilistic Inductive Logic Programming : Theory and Applications
Publication year: 2008
: 978-3-540-78652-8
One of the key open questions within arti?cial intelligence is how to combine probability and logic with learning. This question is getting an increased tentioninseveral disciplines suchas knowledg erepresentation, reasoningabout uncertainty, data mining, and machine learning simulateously,This book providesan introduction to this ?eld with an emphasison those methods based on logic programming principles. The book is also the main result of the successful European ISTFET projectno.FP6-508861on Applition of ProbabilisticInductive Logic Programming (APRILII,2004-2007).It was concerned with theory, implementation sand applications of probabilisticinductivelogic programming.
: Computer Science, Bayesian networks, Kernel, algorithmic learning, classifier systems, clustering, computational biology, constraint logic programming, genetic programming, inductive logic programmi, knowledge, learning, logic, logic programming, machine learning, programming, algorithm analysis and problem complexity
