Building knowledge systems in A -Prolog
Abstract
This work is written in the context of the logic-based approach to Artificial Intelligence (AI) proposed by John McCarthy in 1959 [134]. According to this approach an agent should have knowledge of its world and its goals, and the ability to use this knowledge to infer its course of action. This logic-based method suggests that a mathematical model of an agent should contain: a formal language capable of expressing commonsense knowledge about the world, a precise characterization of valid conclusions which can be derived from theories stated in this language, and a means which will allow the agent to arrive at these conclusions. The purpose of this dissertation is to investigate the applicability of one such language, A-Prolog [71, 73], for the development of medium-size knowledge-intensive systems. A-Prolog is a declarative logic programming language based on stable models/answer sets semantics of logic programs [74, 75]. It allows the representation of defaults and several interesting aspects of reasoning about actions and their effects. There is a recently developed methodology of representing knowledge in A-Prolog, and there are also rather efficient inference engines associated with the language. Our goal was to test this methodology and these inference engines on sizeable engineering applications. In this dissertation, we developed two such applications. The first is a small system, designed as a classroom tool for teaching digital circuits, which allows the functional and behavioral representation of these circuits at the gate-level of abstraction. The second is a substantially larger application—the implementation of a decision support system for the space shuttle's flight controllers. This work involved the representation of a substantial amount of knowledge about the shuttle as well as the execution of complex planning (and other reasoning) tasks. The project was successful, and the system is now in the hands of United Space Alliance (USA), the company responsible for overseeing the operation of the space shuttle. This dissertation describes the design and implementation of these systems and discusses some lessons derived from this experience. We believe that the lessons can be of interest to AI researchers working in the areas of knowledge representation, nonmonotonic reasoning, and planning, as well as to software engineers involved in the construction of knowledge-intensive systems.
Subject Area
Computer science|Artificial intelligence
Recommended Citation
Nogueira, Monica De Lima, "Building knowledge systems in A -Prolog" (2005). ETD Collection for University of Texas, El Paso. AAI3167938.
https://scholarworks.utep.edu/dissertations/AAI3167938