Showing papers in "Artificial Intelligence in 1992"

TL;DR: In this article, the min-conflicts heuristic is used to minimize the number of constraint violations after each step in a value-ordering heuristic search, which can be used with a variety of different search strategies.

TL;DR: It is shown that while the problem of deciding satisfiability of an S5 formula with one agent is NP-complete, the problem for many agents is PSPACE-complete and the problem becomes complete for exponential time once a common knowledge operator is added to the language.

TL;DR: It is argued that any reasonable nonmonotonic inference procedure should define a rational relation and it is shown that the rational relations are exactly those that may be represented by a ranked preferential model, or by a (nonstandard) probabilistic model.

TL;DR: A generalization of Allen's interval-based approach to temporal reasoning is presented and the notion of ‘conceptual neighborhood’ of qualitative relations between events is central to the presented approach, using semi-intervals rather than intervals as the basic units of knowledge.

TL;DR: A general model of partial constraint satisfaction is proposed and standard backtracking and local consistency techniques for solving constraint satisfaction problems can be adapted to cope with, and take advantage of, the differences between partial and complete constraint satisfaction.

TL;DR: In this article, two algorithms for behavior learning are described that combine Q learning, a well-known scheme for propagating reinforcement values temporally across actions, with statistical clustering and Hamming distance.

TL;DR: The “Gibbs sampling” simulation procedure for “sigmoid” and “noisy-OR” varieties of probabilistic belief networks can support maximum-likelihood learning from empirical data through local gradient ascent.

TL;DR: This paper proposes a new concept, that of kernel diagnosis, which is free of this problem with minimal diagnosis and considers restricting the axioms used to describe the system to ensure that the concept of minimal diagnosis is adequate.

TL;DR: This thesis presents a formally precise, elegant, clean, well-defined system which exhibits a correct behavior when applied to the benchmark examples in the literature and represents a definite improvement over past systems.

TL;DR: It is proved that AC-5, in conjuction with node consistency, provides a decision procedure for these constraints running in time $O(ed)$ and has an important application in constraint logic programming over finite domains.

TL;DR: In this paper, the complexity of updating or revising propositional knowledge bases under the principle of Minimal Change was studied, and the complexity results for the following problem were derived: given a knowledge base T, an update p, and a formula q, decide whether q is derivable from T ○ p, the updated (or revised) knowledge base.

TL;DR: A revised algorithm is presented and a proof of its correctness is presented that shows that some diagnoses can be missed under certain conditions.

TL;DR: The construction of a general-purpose defeasible reasoner that is complete for first-order logic and provably adequate for the argument-based conception of defeasibles reasoning that I have developed elsewhere is described.

TL;DR: This paper proposes the beginnings of a theory of reasoning with abstraction which captures and generalizes most previous work in the area and provides the foundations for the mechanization of abstraction inside an abstract proof checker.

TL;DR: It is argued that there are (at least) two useful and quite different ways of understanding belief functions: as a generalized probability function and as a way of representing evidence.

TL;DR: A theory of plan modification applicable to hierarchical nonlinear planning is presented, which utilizes the validation structure of stored plans to yield a flexible and conservative plan modification framework.

TL;DR: This paper defines computationally efficient procedures for solving two related reasoning tasks that arise in interval and point algebras: Given (possibly indefinite) knowledge of the relationships between some intervals or points, find one or more scenarios that are consistent with the information provided, and find all the feasible relations between every pair of interval or points.

TL;DR: It is shown that in the best-known version of the blocks world, planning is difficult, in the sense that finding an optimal plan is NP-hard, but theNP-hardness is not due to deleted-condition interactions, but instead due to a situation which the authors call a deadlock.

TL;DR: In this article, a related technique, tolerance propagation (TP), is proposed to generalize the idea of numerical exact value propagation into interval propagation, which can determine global solutions for interval constraint satisfaction problems with arbitrary accuracy and without losing all attractions of simple local computations.

TL;DR: A new account of defaults, called conditional entailment, is developed, which combines the benefits of the two interpretations of default expressions, and possesses a sound and complete proof theory, based on interacting arguments and amenable to implementation in conventional ATMSs.

TL;DR: The checkers program Chinook has won the right to play a 40-game match for the World Checkers Championship against Dr. Marion Tinsley, the first time a program has earned theright to contest for a human World Championship.

TL;DR: An extension of the Model Elimination theorem proving procedure (SOL-resolution) is presented, providing an effective mechanism complete for finding the characteristic clauses in consequence finding problems within first-order logic.

TL;DR: A new computational model of explanation is presented and it is argued that it results in significant improvements over traditional approaches and also depends on additional knowledge of the domain.

TL;DR: A relationship between the sizes of the variables' domains, the constraints' arity and the level of local consistency sufficient to ensure global consistency is presented and a new tractability classification of constraint networks is presented.

TL;DR: This paper provides a formal theory for plan merging and presents both optimal and efficient heuristic algorithms for finding minimum cost merged plans and demonstrates that efficient and well-behaved approximation algorithms are applicable for optimizing plans with large sizes.

TL;DR: This paper reviews different ways of describing expert system reasoning, emphasizing the use of simple logic, set, and graph notations for making dimensional analyses of modeling languages and inference methods.

TL;DR: This paper describes how the CLP language cc(FD), a successor of CHIP using consistency techniques over finite domains, can be used to solve two practical applications: test-pattern generation and car sequencing.

TL;DR: A fast algorithm for solving qualitative interval constraint problems, which returns solutions of random problems in less than half a second on average, with the hardest problem taking only half a minute on a RISC workstation is presented.

TL;DR: It is shown that the consistency based approach can emulate abductive reasoning by adding closure axioms to a causal theory; and that abductive techniques can be used in place of the consistencybased method in the domain of logic based diagnosis.