T h e level o f abs t rac t ion of m u c h of the w o r k in know ledge-based systems ( the ru le , f rame, logic level) is too low to prov ide a r ich enough vocabu la ry for knowledge and con t ro l . I prov ide an overv iew of a f r amework cal led the Generic Task approach that proposes t h a t knowledge systems shou ld be b u i l t out of b u i l d i n g blocks, each of wh ich is app rop r i a te for a basic t ype of p rob lem so lv ing. Each generic task uses forms of knowledge and cont ro l strategies that are character is t ic to i t , and are general ly conceptua l ly closer to doma in knowledge. Th i s fac i l i ta tes knowledge acqu is i t i on , and can produce a more perspicuous exp lana t ion of p rob lem so lv ing . The re la t ionsh ip of the const ructs at the generic task level to the ru le f rame level is analogous to t h a t between h igh level p r o g r a m m i n g languages and assembly languages. 1 describe a set of generic tasks t ha t have been found pa r t i cu la r l y useful in cons t ruc t i ng d iagnost ic , design and p lann ing systems; d iagnost ic reasoning is used to i l lus t ra te the approach . 1 describe the Generic Task Toolset for cons t ruc t i ng knowledge systems, w h i c h embodies the Generic Task app roach . I conclude w i t h the imp l i ca t i ons of this approach for the func t iona l a rch i tec ture of in te l l igence. 1. Overview of the Paper T h e f i rst pa r t of the paper is a c r i t i que of the level o f abs t rac t ion in much of the cu r ren t discussion on knowledge-based systems. I t w i l l be argued t ha t the level of ru leslog icf rames-networks is i napp rop r i a te for d iscussing m a n y issues of knowledge o rgan iza t ion and c o n t r o l . We advocate instead the level of abs t rac t ion associated w i t h the language of generic tasks, types of knowledge, and types of con t ro l

/pdf/towards-a-functional-architecture-for-intelligence-based-on-zo2w8t3yo5.pdf

Towards a functional architecture for intelligence based on generic information processing tasks

A general problem-solving mechanism is described that is especially suited for performing a particular form of abductive inference, or best explanation finding. A problem solver embodying this mechanism synthesizes composite hypotheses by combining simple hypotheses to satisfy explanatory goals. These simple hypotheses are formed by instantiating prestored explanatory "concepts." In this way the problem solver is able to arrive at complex integrated conclusions which are not prestored. A computationally feasible task-specific problem-solving mechanism is presented for a particular information-processing task which is, nevertheless, of very great generality. The task is that of synthesizing coherent composite explanatory hypotheses based upon a prestored and possibly vast collection of hypothesis-generating concepts. This is seemingly a common task of intelligence and potentially a major component of diagnostic reasoning, especially where single-fault assumptions are inappropriate. The mechanism is described both functionally and structurally; that is, the why and what of the main computations are described, together with algorithms that show how each of these computations can be accomplished. The mechanism integrates a classification machine, used for selecting plausible hypotheses, with a specialized means-ends machine, used for assembling a best explanation from the plausible hypotheses thus selected and for pointedly investigating alternative explanations. There are also two other specialized mechanisms for the subsidiary functions of recognizing the applicability of a hypothesis to the situation and of interpreting the situation-specific raw data to satisfy the informational needs of the other components.

A Mechanism for Forming Composite Explanatory Hypotheses

The level of abstraction of much of the work in knowledge-based systems (the rule, frame, logic level) is too low to provide a rich enough vocabulary for knowledge and control. I provide an overview of a framework called the Generic Task approach that proposes that knowledge systems should be built out of building blocks, each of which is appropriate for a basic type of problem solving. Each generic task uses forms of knowledge and control strategies that are characteristic to it, and are in general conceptually closer to domain knowledge. This facilitates knowledge acquisition and can produce a more perspicuous explanation of problem solving. The relationship of the constructs at the generic task level to the rule-frame level is analogous to that between high-level programming languages and assembly languages in computer science. I describe a set of generic tasks that have been found particularly useful in constructing diagnostic, design and planning systems. In particular, I describe two tools, CSRL and DSPL, that are useful for building classification-based diagnostic systems and skeletal planning systems respectively, and a high level toolbox that is under construction called the Generic Task toolbox.

Generic tasks as building blocks for knowledge-based systems: the diagnosis and routine design examples

In this article, we present a programming language for expressing classificatory problem solvers. CSRL (Conceptual Structures Representation Language) provides structures for representing classification trees, for navigating within those trees, and for encoding uncertainly judgments about the presence of hypotheses. We discuss the motivations, theory, and assumptions that underlie CRSL. Also, some expert systems constructed with CSRL are briefly described.

/pdf/crsl-a-language-for-classificatory-problem-solving-and-1i0xu2jhy0.pdf

CRSL: A language for classificatory problem solving and uncertainty handling

The present invention provides methods and apparatus for the application of a particle array in bioassay format to perform qualitative and/or quantitative molecular interaction analysis between two classes of molecules (an analyte and a binding agent). The methods and apparatus disclosed herein permit the determination of the presence or absence of association, the strength of association, and/or the rate of association and dissociation governing the binding interactions between the binding agents and the analyte molecules. The present invention is especially useful for performing multiplexed (parallel) assays for qualitative and/or quantitative analysis of binding interactions of a number of analyte molecules in a sample.

Multianalyte molecular analysis using application-specific random particle arrays

We describe a software module in an expert system RED, which interprets data related to red cell antibody identification. There are three portions to this module: (1) the problem-solving component, which incorporates the knowledge required for antibody identification as a hierarchy of programs. The programs in the hierarchy organize within themselves small pieces of knowledge represented in the form of production rules, which are capable of making judgments concerning a specific hypothesis; (2) an intelligent data base for storage of patient data, red cell attributes, and test results; (3) the “overview critic” portion, which combines the atomic hypotheses judged favorably by the antibody programs into a unified judgment concerning the case. Overview makes the decision to terminate processing with a conclusion about which antibodies are actually present and what specific further tests need to be performed to resolve any remaining ambiguities.

RED: A red-cell antibody identification expert module

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RED: A red-cell antibody identification expert module