The complexity of theory revision
DOI10.1016/S0004-3702(98)00107-6zbMath0996.68068WikidataQ127526104 ScholiaQ127526104MaRDI QIDQ1606294
Publication date: 24 July 2002
Published in: Artificial Intelligence (Search for Journal in Brave)
Analysis of algorithms and problem complexity (68Q25) Logic in artificial intelligence (68T27) Logics of knowledge and belief (including belief change) (03B42) Reasoning under uncertainty in the context of artificial intelligence (68T37) Theory of languages and software systems (knowledge-based systems, expert systems, etc.) for artificial intelligence (68T35) Complexity of computation (including implicit computational complexity) (03D15)
Related Items (2)
Uses Software
Cites Work
- Results on learnability and the Vapnik-Chervonenkis dimension
- Foundations of a functional approach to knowledge representation
- Completeness in approximation classes
- Quantifying inductive bias: AI learning algorithms and Valiant's learning framework
- Knowing what doesn't matter: exploiting the omission of irrelevant data
- Estimation of dependences based on empirical data. Transl. from the Russian by Samuel Kotz
- Abductive explanation-based learning: A solution to the multiple inconsistent explanation problem
- On the complexity of propositional knowledge base revision, updates, and counterfactuals
- Structure identification in relational data
- Theory refinement combining analytical and empirical methods
- The refinement of probabilistic rule sets: Sociopathic interactions
- Polynomial-time inference of all valid implications for Horn and related formulae
- Refinement of uncertain rule bases via reduction
- A general lower bound on the number of examples needed for learning
- Horn approximations of empirical data
- Belief revision: A critique
- Learnability and the Vapnik-Chervonenkis dimension
- On the logic of theory change: Partial meet contraction and revision functions
- The complexity of revising logic programs
- On the hardness of approximating minimization problems
- A Measure of Asymptotic Efficiency for Tests of a Hypothesis Based on the sum of Observations
- Pac-learning non-recursive Prolog clauses
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
This page was built for publication: The complexity of theory revision