44387886
Fuzzy logic or Lukasiewicz logic: A clarification
Abstract We discuss some issues on fuzzy logic developed by Pavelka [Z. Math. Logic 25 (1979) 45–52, 119–134, 447–464] vs. the many-valued Lukasiewicz's logic. The focus is on the proper choice of fuzzy implication operations, a question which has been addressed many times in the fuzzy research literature. Pavelka had shown in 1979 that the only natural way of formalizing fuzzy logic for truth values in the unit interval [0, 1] is by using Lukasiewicz's implication operator a → b = min {1, 1 - a + b } or some isomorphic form of it. Many other papers around the same time had attempted to formulate alternative definitions for a → b by giving intuitive justifications. There continues to be some confusion, however, even today about the right notion of fuzzy logic. Much of this confusion lies in the use of improper “an” (“or”) and the “not” operations and a misunderstanding of some of the key differences between “proofs” or inferencing in fuzzy logic and those in Lukasiewicz's logic. We point out the need for defining the strong conjunction operator “⊗” in connection with fuzzy Modus-ponens rule and why we do not need the fuzzy Syllogism inference rule. We formulate two requirements of the fuzzy implication operator, which are satisfied by Lukasiewicz's a → b , but which fail for many of the alternative definitions for “→”.
39684197
A sound and complete proof theory for the generalized logic of only knowing
We present a sound and complete proof theory for the generalized logic of only knowing (GOL). The GOL logic is a modal logic proposed recently (Chen 1997) as a unified logical framework for non-monotonic reasoning, which extends the logic of only knowing (OL) of Levesque (1990), and covers the important notion of epistemic specification (Gelfond 1991, Gelfond and Przymusinska 1993) which is very useful for knowledge representation. The OL logic has been shown to have close connections with Lifschitz's minimal belief and negation as failure (Lifschitz 1994) and various other major non-monotonic formalisms. The GOL logic is more general and powerful than OL. The completeness result for the GOL proof theory establishes the theoretical foundation for answering queries in epistemic theories. This work is restricted to the propositional case only.
27866706
A New Method of Circumscribing Beliefs: The Propositional Case
We propose here a new notion of a minimal model for forming circumscription in belief-logic by incorporating the notion of minimal models in the prepositional logic. This results in a new circumscription operation for belief-formulas than the one considered in [4-6]. An important feature of the new circumscription operation is its close relationship with the circumscription of prepositional formulas. For instance, we have CIRC[Bp] = B(CIRC[p]), where p is a prepositional formula. We give several examples to show that the new notion of circumscription fits quite well with intuition.
14245135
Automatic Correlation and Calibration of Noisy Sensor Readings Using Elite Genetic Algorithms
This paper explores an image processing application of optimization techniques which entails interpreting noisy sensor data. The application is a generalization of image correlation; we attempt to find the optimal gruence which matches two overlapping gray scale images corrupted with noise. Both tabu search and genetic algorithms are used to find the parameters which match the two images. A genetic algorithm approach using an elitist reproduction scheme is found to provide significantly superior results.
38658502
Learning by Discovering Problem Solving Heuristics Through Experience
The authors present a system, called SAFE (strategy acquisition from experience), which incorporates novel methods for discovering domain-dependent problem-solving heuristics. SAFE is implemented as a sorting system whose sorting strategies are represented as production rules. SAFE initially uses the insertion sort strategy to solve problems. After solving each given problem. SAFE learns symbolic rules from the solution path which is obtained by applying the existing heuristic information. By one or several processes of learning. SAFE is able to obtain the heuristics to sort new problems with minimum exchanges of elements. The notion of shortcut, an effective inductive learning bias for reducing the hypothesis space to be searched during learning, is introduced. >
31224210
The strong semantics for logic programs
Recently, the well-founded semantics of a logic programP has been strengthened to the well-founded semantics-by-case (WFC) and this in turn has been strengthened to the extended well-founded semantics (WFE). Both WFC(P) and WFE(P) have thelogical consequence property, namely, if an atomAj is true in the theory Th(P), thenAj is true in the semantics as well. However, neither WFC nor WFE has the GCWA property, i.e., if an atomAj is false in all minimal models ofP,Aj may not be false in WFC(P) (resp. WFE(P)). We extend the ideas in WFC and WFE to define a strong well-founded semantics WFS which has the GCWA property. The strong semantics WFS(P) is defined by combining GCWA with the notion ofderived rules. Here we use a new Type-III derived rules in addition to those used in WFC and WFE. The relationship between WFS and WFC is also clarified.
117657252
Labeled Search Trees and Amortized Analysis: Improved Upper Bounds for NP-Hard Problems
A sequence of exact algorithms to solve the Vertex Cover and Maximum Independent Set problems have been proposed recently in the literature. All these algorithms appeal to a very conservative analysis that considers the size of the search tree, under a worst-case scenario, to derive an upper bound on the running time of the algorithm. In this paper we propose a different approach to analyze the size of the search tree. We use amortized analysis to show how simple algorithms, if analyzed properly, may perform much better than the upper bounds on their running time derived by considering only a worst-case scenario. This approach allows us to present a simple algorithm of running time O(1.194 k + n) for the parameterized Vertex Cover problem on degree-3 graphs, and a simple algorithm of running time O(1.1254 n ) for the Maximum Independent Set problem on degree-3 graphs. Both algorithms improve the previous best algorithms for the problems.
7457791
Choosing Among Alternative Futures
Non-determinism is a serious impediment to testing and debugging concurrent programs. Such programs do not execute the same way each time they are run, which can hide the presence of errors. Existing techniques use a variety of mechanisms that attempt to increase the probability of uncovering error conditions by altering the execution sequence of a concurrent program, but do not test for specific errors. This paper presents some preliminary work in deterministically executing a multithreaded program using a combination of an intermediate compiler form that identifies the set of writes of a shared variable by other threads are visible at a given read of that variable and aspect-oriented programming to control program execution. Specifically, the aspects allow a read of a shared variable to return any of the reaching definitions, where the desired definition can be selected before the program is run. As a result, we can deterministically run test cases. This work is preliminary and many issues have yet to be resolved, but we believe this idea shows some promise.
2647804
Extended DBP for (m, k)-Firm Based QoS
In this paper, an extended DBP (E_DBP) scheme is studied for (m,k)-firm constraint. The basic idea of the proposed algorithm takes into account the distance to exit a failure state, which is a symmetrical notion of distance to fall into a failure state in DBP. Quality of Service (QoS) in terms of dynamic failure and delay is evaluated. Simulation results reveal the effectiveness of E_DBP to provide better QoS.
16407407
An interactive method for fuzzy multiple attribute group decision making
In this paper, we develop an interactive method for multiple attribute group decision making under fuzzy environment. The method can be used in situations where the information about attribute weights is partly known, the weights of decision makers are expressed in exact numerical values or triangular fuzzy numbers, and the attribute values are triangular fuzzy numbers. The method transforms fuzzy decision matrices into their expected decision matrices, constructs the corresponding normalized expected decision matrices by two simple formulas, and then aggregates these normalized expected decision matrices into a complex decision matrix. Moreover, the decision makers are asked to provide their preferences gradually in the course of interactions. By solving linear programming models, the method diminishes the given alternative set gradually, and finally finds the most preferred alternative. By using the method, the decision makers can provide and modify their preference information gradually in the process of decision making so as to make the decision result more reasonable. The method can not only reflect the importance of the given arguments and the ordered positions of the arguments, but also relieve the influence of unfair arguments on the decision result. Finally, a practical problem is used to illustrate the developed method.
12280706
A distributed multi-agent system for collaborative information management and sharing
In this paper, we present DIAMS, a system of distributed, collaborative agents to help users access, manage, share and exchange information. A DIAMS personal agent helps its owner find information most relevant to current needs. It provides tools and utilities for users to manage their information repositories with dynamic organization and virtual views. Flexible hierarchical display is integrated with indexed query search to support effective information access. Automatic indexing methods are employed to support user queries and communication between agents.