Multi-Dimensional Inheritance

In this paper, we present an alternative approach to multiple inheritance for typed feature structures. In our approach, a feature structure can be associated with several types coming from different hierarchies (dimensions). In case of multiple inheritance, a type has supertypes from different hierarchies. We contrast this approach with approaches based on a single type hierarchy where a feature structure has only one unique most general type, and multiple inheritance involves computation of greatest lower bounds in the hierarchy. The proposed approach supports current linguistic analyses in constraint-based formalisms like HPSG, inheritance in the lexicon, and knowledge representation for NLP systems. Finally, we show that multi-dimensional inheritance hierarchies can be compiled into a Prolog term representation, which allows to compute the conjunction of two types efficiently by Prolog term unification.Comment: 9 pages, styles: a4,figfont,eepic,eps

Disjunctive Logic Programs with Inheritance

The paper proposes a new knowledge representation language, called DLP<, which extends disjunctive logic programming (with strong negation) by inheritance. The addition of inheritance enhances the knowledge modeling features of the language providing a natural representation of default reasoning with exceptions. A declarative model-theoretic semantics of DLP< is provided, which is shown to generalize the Answer Set Semantics of disjunctive logic programs. The knowledge modeling features of the language are illustrated by encoding classical nonmonotonic problems in DLP<. The complexity of DLP< is analyzed, proving that inheritance does not cause any computational overhead, as reasoning in DLP< has exactly the same complexity as reasoning in disjunctive logic programming. This is confirmed by the existence of an efficient translation from DLP< to plain disjunctive logic programming. Using this translation, an advanced KR system supporting the DLP< language has been implemented on top of the DLV system and has subsequently been integrated into DLV.Comment: 28 pages; will be published in Theory and Practice of Logic Programmin

A knowledge based software engineering environment testbed

The Carnegie Group Incorporated and Boeing Computer Services Company are developing a testbed which will provide a framework for integrating conventional software engineering tools with Artifical Intelligence (AI) tools to promote automation and productivity. The emphasis is on the transfer of AI technology to the software development process. Experiments relate to AI issues such as scaling up, inference, and knowledge representation. In its first year, the project has created a model of software development by representing software activities; developed a module representation formalism to specify the behavior and structure of software objects; integrated the model with the formalism to identify shared representation and inheritance mechanisms; demonstrated object programming by writing procedures and applying them to software objects; used data-directed and goal-directed reasoning to, respectively, infer the cause of bugs and evaluate the appropriateness of a configuration; and demonstrated knowledge-based graphics. Future plans include introduction of knowledge-based systems for rapid prototyping or rescheduling; natural language interfaces; blackboard architecture; and distributed processin

A GENERIC SHELL APPROACH FOR KMOWLEDGE ELICITATION AMD REPRESENTATION IM IDSS

This study focuses on issues of knowledge representation and elicitation in Intelligent DSS (IDSS) environments. The types, characteristics, levels of logical view, and the levels of specificity and abstraction of passive and active knowledge in IDSS are discussed. A language for knowledge description, whose syntactical objects are entities, relationships, transformations, and constraints, and which allows four levels of specificity and abstraction is proposed. Then, a graphical, semantic model for the conceptual-schema representation of passive and active knowledge, called the extended ERA Model, is presented. Finally, it is argued that a multi-paradigm programming environment is required for the information-schema representation of the different types of knowledge in IDSS, and to support reasoning, inference, and inheritance. A LOOPS implementation of the knowledge representation and elicitation model is described in detail

Approximate reasoning using terminological models

Term Subsumption Systems (TSS) form a knowledge-representation scheme in AI that can express the defining characteristics of concepts through a formal language that has a well-defined semantics and incorporates a reasoning mechanism that can deduce whether one concept subsumes another. However, TSS's have very limited ability to deal with the issue of uncertainty in knowledge bases. The objective of this research is to address issues in combining approximate reasoning with term subsumption systems. To do this, we have extended an existing AI architecture (CLASP) that is built on the top of a term subsumption system (LOOM). First, the assertional component of LOOM has been extended for asserting and representing uncertain propositions. Second, we have extended the pattern matcher of CLASP for plausible rule-based inferences. Third, an approximate reasoning model has been added to facilitate various kinds of approximate reasoning. And finally, the issue of inconsistency in truth values due to inheritance is addressed using justification of those values. This architecture enhances the reasoning capabilities of expert systems by providing support for reasoning under uncertainty using knowledge captured in TSS. Also, as definitional knowledge is explicit and separate from heuristic knowledge for plausible inferences, the maintainability of expert systems could be improved

Computing Specificity

This note reports on an effort to implement a version of Poole\u27s rule for specificity. Relatively, efficient implementation relies on correcting and improving a pruning lemma of Simari-Loui [92]. This in turn requires revision of Poole\u27s specificity concept. The resulting system is a usable knowledge representation system with first-order-language and defeasible reasoning. Sample input and output are included in an appendix. It is a good candidate for multiple inheritance applications; it is useful for planning, but limited by the underlying search for plans

Inheritance hierarchies and historical reconstruction: towards a history of Slavonic colour terms

The last decade has witnessed an interest in inheritance hierarchies for the representation of linguistic knowledge. An obvious application is to historical reconstruction of a language family, but this is largely unexplored territory. We demonstrate the merits of such an approach with a default inheritance treatment of the colour terms of Slavonic: Slavonic because it is uncontroversially a genetic unit, and colour terms both because of their universality and because of the tight constraints on a language\u27s colour term inventory (Berlin & Kay 1969, and subsequent work). In section I we discuss the colour terms of Slavonic and introduce Berlin and Kay\u27s typology and the notion of basic colour term. Section 2 describes our methodology and in section 3 we show how it is applied to Slavonic. The main results are discussed in section 4

HEALTH DISPARITIES: THE GENETIC CONTRIBUTION IN THE AFRICAN AMERICAN COMMUNITY

poster abstractSince the completion of the Human Genome Project, it has been found that genes and their function play a role in 9 out of 10 of the leading causes of death in the U.S. Some of these causes such as heart disease, cancer, stroke and diabetes are significantly prevalent in the African American community. African Americans often experience the largest differences in health risks when compared to their White counterparts. This research project will examine how mutated genes and their function, contribute to health disparities in the African American community. The population for this research project will only include individuals of African ancestry born in the U.S. A brief survey will be conducted to inquire about participants’ knowledge of genetics and its influence on disease inheritance. The data collected will be interpreted as a representation of average African Americans’ knowledge of genetic influences on disease inheritance. Additionally, data will be obtained from facilities that offer genetic testing services. Specifically, I hope to obtain information on the racial populations who utilize these services, primarily, those with higher occurrences of genetic disorders. Coupled with the survey’s data, I will use the testing centers’ information to determine whether a correlation exists between the following variables: knowledge of genetics, use of genetic testing services and prevalence of inheritable diseases. I expect a strong correlation between afore mentioned variables. My hypothesis is that this correlation will prove undetected gene mutations when inherited, contribute to health disparities in the African American community