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.
30548729
A Class of Stratified Programs in Autoepistemic Logic of Knowledge and Belief
Przymusinski proposed [11] AELB, the autoepistemic logic of knowledge and belief. The AELB logic is a very powerful and expressive formal system which isomorphically contains various major non-monotonic knowledge representation formalisms and major logic program semantics. Thus AELB can be used as a unifying framework for non-monotonic knowledge representation formalisms, which allows us to compare and better understand different formalizations of common-sense knowledge.
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.
9144862
Rules and fuzzy rules in text: concept, extraction and usage
Several concepts and techniques have been imported from other disciplines such as Machine Learning and Artificial Intelligence to the field of textual data. In this paper, we focus on the concept of rule and the management of uncertainty in text applications. The different structures considered for the construction of the rules, the extraction of the knowledge base and the applications and usage of these rules are detailed. We include a review of the most relevant works of the different types of rules based on their representation and their application to most of the common tasks of Information Retrieval such as categorization, indexing and classification.
38425768
The Logic of Only Knowing as a Unified Framework for Non-Monotonic Reasoning
We propose to use the logic of only knowing (OL) by Levesque [6] as a unified framework that encompasses various non-monotonic formalisms and logic programming. OL is a modal logic which can be used to formalize an agent's introspective reasoning and to answer epistemic queries to databases. The OL logic allows one to formally express the statement “α is all I know” (in symbols, Oα) and to perform inferencing based on only-knowing, which is very useful for commonsense reasoning. Another nice thing about the OL logic is that it has a clear model-theoretic semantics and a simple proof theory, which is sound for the quantificational case, and both sound and complete for the prepositional case.
27409853
The Strong Semantics for Logic Programs
Recently, the well-founded semantics of a logic program P has been strengthened to the well-founded semantics-by-case (WF C ) and then again to the extended well-founded semantics (WF E ). An important concept used in both WF C and WF E is that of derived rules. We extend the notion of derived rules by adding a new type of derivation and define the strong semantics of P, which has the following important property, known as the GCWA-property: if an atom p = false in all minimal models of P, then p = false in the strong semantics of P. In general, the WF C -semantics and the WF E -semantics do not have the GCWA-property. If we first apply the WF E -semantics to P and then apply the strong semantics to a suitably simplified form of P based on its WF E -semantics, then the resulting semantics is stronger than the WF E -semantics and has the GCWA-property.
10895534
Aspect-Based Instrumentation for Locating Memory Leaks in Java Programs
Despite the built-in garbage collector, Java programs can still suffer the memory leak problem resulted from the unhealthy programming style of retaining unwanted references. This paper presents an aspect-based tool for assisting programmers in locating such references to fix the problem. This tool, FindLeaks, utilizes an aspect to collect memory consumption statistics and object references created during a program's execution and analyzes them for detecting memory leaks. The distinctive feature of FindLeaks is that it reports not only suspected classes of leaking objects but also where in the source the unwanted references were created. Besides, this paper also reports some preliminary experience with FindLeaks.
35624108
Optimal Parallel Routing in Star Graphs
Star graphs have been recently proposed as attractive alternatives to the popular hypercube for interconnecting processors on a parallel computer. In this paper, we present an efficient algorithm that constructs an optimal parallel routing in star graphs. Our result improves previous results for the problem.
784309
Learning subjective relevance to facilitate information access
As the amount of available electronic information is dramatically increasing, the ability for rapid and e ective access to information has become critical. Most traditional information access methods rely on measures of relevance based on information content. We propose a new approach which augments existing information access methods with subjective relevance learned from user feedback. We developed an adaptive system which helps users access information by employing learned knowledge about which documents are likely to be relevant, given the current user's information need and user pro le. This system is based on a model, called a relevance network, which learns and generalizes relevance information in a rapid, cost-e ective, and incremental manner. We present the design of the relevance network and results of experimental evaluation.
20277412
Adaptive hypertext navigation based on user goals and context
Hypertext systems allow flexible access to topics of information, but this flexibility has disadvantages. Users often become lost or overwhelmed by choices. An adaptive hypertext system can overcome these disadvantages by recommending information to users based on their specific information needs and preferences. Simple associative matrices provide an effective way of capturing these user preferences. Because the matrices are easily updated, they support the kind of dynamic learning required in an adaptive system.HYPERFLEX, a prototype of an adaptive hypertext system that learns, is described. Informal studies with HYPERFLEX clarify the circumstances under which adaptive systems are likely to be useful, and suggest that HYPERFLEX can reduce time spent searching for information by up to 40%. Moreover, these benefits can be obtained with relatively little effort on the part of hypertext authors or users.The simple models underlying HYPERFLEX's performance may offer a general and useful alternative to more sophisticated modelling techniques. Conditions under which these models, and similar adaptation techniques, might be most useful are discussed.
31594321
Hypercube Network Fault Tolerance: A Probabilistic Approach
Extensive experiments and experience have shown that the well-known hypercube networks are highly fault tolerant. What is frustrating is that it seems very difficult to properly formulate and formally prove this important fact, despite extensive research efforts in the past two decades. Most proposed fault tolerance models for hypercube networks are only able to characterize very rare extreme situations thus significantly underestimating the fault tolerance power of hypercube networks, while for more realistic fault tolerance models, the analysis becomes much more complicated. In this paper, we develop new techniques that enable us to analyze a more realistic fault tolerance model and derive lower bounds for the probability of hypercube network fault tolerance in terms of node failure probability. Our results are both theoretically significant and practically important. From the theoretical point of view, our method offers very general and powerful techniques for formally proving lower bounds on the probability of network connectivity, while from the practical point of view, our results provide formally proven and precisely given upper bounds on node failure probabilities for manufacturers to achieve a desired probability for network connectivity. Our techniques are also useful and powerful for analysis of the performance of routing algorithms, and applicable to the study of other hierarchical network structures and to other network communication problems.