A deduction system, called RE-proof system, is constructed for generating the revisions of first order belief sets. When a belief set is rejected by a given fact, all maximal subsets of the belief set consistent with the fact can be deduced from the proof system. The soundness and completeness of the RE-proof system are proved, which imply that there exists a resolution method to decide whether a revision retains a mtalmal subset of a belief set.

The aim of this paper is to extend the system of belief revision developed by Alchourron, Gardenfors and Makinson (AGM) to a more general framework.This extension enables a treatment of revision not only by single sentences but also by any sets of sentences, especially by infinite sets. The extended revision and contraction operators will be called general ones, respectively. A group of postulates for each operator is provided in such a way that it coincides with AGM's in the limit case. A notion of the nic…

In this paper some undecidable problems on approximability of NP op-timization problems are investigated. In particular, the following problems are all undecidable: (1) Given an NP optimization problem, is it approal-mable in polynomial time? (2) For any polynomialtime computable function r(n), given a polynomial time approkimable NP optimization problem, has it a polynomialtime approximation algorithm with approkimation performance ratio r(n) (r(n)-approkimable)? (3) For any polynomial-time computable func…

This paper proposes NNF - a fuzzy Petri Net system based on neural network for proposition logic representation, and gives the formal definition of NNF. For the NNF model, forward reasoning algorithm, backward reason-ing algorithm and knowledge learning algorithm are discussed based on weight training algorithm of neural network - Back Propagation algorithm. Thus NNF is endowed with the ability of learning a rule. The paper concludes with a discussion on extending NNF to predicate logic, forming NNPrF, and …

Multimedia data include text, image, audio and video, etc. Recent deve-lopments and advances in the areas of mass storage technology and high speed networks make it feasible for multimedia computing systems to offer services such as multimedia e-mail, teleconferencing and various vivid games. The stor-age and retrieval of multimedia data are two of the most important technologies in the future multimedia systems. This paper analyzes the synchronization re-quirements of the delay-sensitive media streams, cla…

Contextual logic provides a mechanism to reason about modules. In this paper, this theory of modules is extended to a context theory of classes where class is in the true spirit of object-oriented databases. The logic, referred to as CLOG,is class-based. CLOG supports class, object identity, multiple role of object,monotonic and non-monotonic inheritance of data a-nd method, method factor-ing, views, derived and query classes. Views and derived classes are queries in themselves- Objects are pure data terms …

Based on the previous work, some necessary conditions of the two-level Uncertainty Reasoning Model (URM) are proposed and an improvement on the twcalevel Uan is made that can describe and process the deviation. In addition, the paper presents two theorems for specifying the correctness about the improvement. Finally, the application of the twrvlevel URM is discussed.

This paper proposes the use of the current signal to express logic values and establishes the theory of grounded current switches suitable for I2L circuits.Based on the advantage that current signals are easy to be added, the design technique of I2L circuits by means of the multi-valued current signal is proposed.It is shown that simpler structure of I2L circuits can be obtained with this technique.

Reasoning about action is an important aspect of common sense reasoning and planning. It gives rise to three classical problems: the frame problem,the qualification problem and the ramification problem. Ekisting approaches cannot deal with these problems efficiently. This paper presents a new method which uses the stratified ATMS for reasoning about action to overcome the limitations of these approaches.