Artificial Intelligence Research Branch future plans

This report contains information on the activities of the Artificial Intelligence Research Branch (FIA) at NASA Ames Research Center (ARC) in 1992, as well as planned work in 1993. These activities span a range from basic scientific research through engineering development to fielded NASA applications, particularly those applications that are enabled by basic research carried out in FIA. Work is conducted in-house and through collaborative partners in academia and industry. All of our work has research themes with a dual commitment to technical excellence and applicability to NASA short, medium, and long-term problems. FIA acts as the Agency's lead organization for research aspects of artificial intelligence, working closely with a second research laboratory at the Jet Propulsion Laboratory (JPL) and AI applications groups throughout all NASA centers. This report is organized along three major research themes: (1) Planning and Scheduling: deciding on a sequence of actions to achieve a set of complex goals and determining when to execute those actions and how to allocate resources to carry them out; (2) Machine Learning: techniques for forming theories about natural and man-made phenomena; and for improving the problem-solving performance of computational systems over time; and (3) Research on the acquisition, representation, and utilization of knowledge in support of diagnosis design of engineered systems and analysis of actual systems

A survey of program transformation with special reference to unfold/fold style program development

This paper consists of a survey of current, and past, work on *program transformation* for the purpose of optimization. We first discuss some of the general methodological frameworks for program modification, such as *analogy*, *explanation based learning*, *partial evaluation*, *proof theoretic optimization*, and the *unfold/fold* technique. These frameworks are not mutually exclusive, and the latter, unfold/fold, is certainly the most widely used technique, in various guises, for program transformation. Thus we shall often have occasion to: compare the relative merits of systems that employ the technique in some form, *and*; compare the unfold/fold systems with those that employ alternative techniques. We also include (and compare with unfold/fold) a brief survey of recent work concerning the use of *formal methods* for program transformation

Proceedings of the Workshop on Change of Representation and Problem Reformulation

The proceedings of the third Workshop on Change of representation and Problem Reformulation is presented. In contrast to the first two workshops, this workshop was focused on analytic or knowledge-based approaches, as opposed to statistical or empirical approaches called 'constructive induction'. The organizing committee believes that there is a potential for combining analytic and inductive approaches at a future date. However, it became apparent at the previous two workshops that the communities pursuing these different approaches are currently interested in largely non-overlapping issues. The constructive induction community has been holding its own workshops, principally in conjunction with the machine learning conference. While this workshop is more focused on analytic approaches, the organizing committee has made an effort to include more application domains. We have greatly expanded from the origins in the machine learning community. Participants in this workshop come from the full spectrum of AI application domains including planning, qualitative physics, software engineering, knowledge representation, and machine learning

An application of formal semantics to student modelling : an investigation in the domain of teaching Prolog

This thesis reports on research undertaken in an exploration of the use of formal semantics for student modelling in intelligent tutoring systems. The domain chosen was that of tutoring programming languages and within that domain Prolog was selected to be the target language for this exploration. The problem considered is one of how to analyse students' errors at a level which allows diagnosis to be more flexible and meaningful than is possible with the 'mal-rules' and 'bugcatalogue' approach of existing systems. The ideas put forward by Robin Milner [1980] in his Calculus of Communicating Systems (CCS) form the basis of the formalism which is proposed as a solution to this problem. Based on the findings of an empirical investigation, novices' misconceptions of control flow in Prolog was defined as a suitable area in which to explore the application of this solution. A selection of Prolog programs used in that investigation was formally described in terms of CCS. These formal descriptions were used by a production rule system to generate a number of the incomplete or faulty models of Prolog execution which were identified in the first empirical study. In a second empirical study, a machine-analysis tool, designed to be part of a diagnostic tutoring module, used these models to diagnose students' misconceptions of Prolog control flow. This initial application of CCS to student modelling showed that the models of Prolog execution generated by the system could be used successfully to detect students' misunderstandings. Results from the research reported here indicate that the use of formal semantics to model programming languages has a useful contribution to make to the task of student modelling

Problem solving from textbook examples

There has been a great deal of research into students' use of examples when solving problems in textbooks. Much of this work has been within the framework of analogical problem solving (APS). Indeed many researchers believe they can build adequate models of how students learn and solve exercise problems by analogy to worked examples. In the first part of this thesis I argue that this view of problem solving from examples is inappropriate and often misleading. Most students learning a subject for the first time tend to imitate examples. Imitative Problem Solving UPS)is a weak form of analogical problem solving. APS accounts assume that a solver has a representation of an earlier problem in memory. The difficulties involved are accessing that source problem and adapting it to solve the current one. WS does not assume t at the source is represented in memory, and even when the source example is available( as in textbook examples), the student may not understand it well enough to be able to adapt it to new situations.The second part of the thesis presents an interpretation theory for analysing both texts and the behaviour of solvers using those texts to solve exercise problems.The third part applies the interpretation theory to the solution explanation of a simple algebra word problem. Where an example problem fails to map directly onto an exercise problem, or where inferences have to be made to understand it, the solver win be unable to imitate the example and hence will have difficulties in proportion to the mapping inequalities between the two problems. That is, the interpretation theory allows us to predict precisely where solvers will have difficulty using an example to solve an exercise problem of the same type.The final part presents experimental tests of these predictions. The results confirm that the interpretation theory analysis can correctly identify possible areas of difficulty for the student due to a) the way an example problem is structured, and b) the nature of the transfer task

A focus on learning : Wuality in teaching & learning : The proceedings of the Teaching & Learning Forum, Edith Cowan University, Perth, February 1995

These papers represent the proceedings of the fourth Teaching and Learning Forum conducted in Perth from February 7-9, 1995. Curtin University hosted the first two Forums and we at Edith Cowan University the third and fourth. In 1996 the honour (and the hard work) transfers to Murdoch. The Forum\u27s objectives were: • To bring together people in higher education who are interested in practical teaching issues (Lecturers, managers, administrators, students, support, general and technical staff). • To share ideas, information and practices in a variety of mutually supportive, friendly and co-operative ways. • To celebrate quality in teaching and learning and raise the status of teaching and learning in tertiary institutions. We believe that these were achieved. This set of proceedings is not organised around a set of sub themes, but rather is presented in alphabetical order with outlines of workshops and short presentations taking their place alongside research papers - as was the case at the Forum