This thesis is concerned with the development of an under-lying model of memory to support selective case retrieval for case-based reasoning. The major requirements are that retrieval should be highly flexible yet efficient. The traditional approach of "indexing" is rejected as being too restrictive while more flexible approaches in analogical reasoning are generally too computationally expensive. Several important organisational principles are developed in the memory model. A network representation is advocated with a number of required extensions; such as multi-granular representation, context-based segregation and a statistically-based grading of paths. The organisation of memory offers the potential for the serial performance of a number of retrieval tasks that have previously only been addressed by assuming a massively parallel implementation. The retrieval mechanism developed is a novel activation passing technique that creates a gradation of stored cases during retrieval. Empiri...

Most work in artificial intelligence and law has concentrated on modelling the type of reasoning done by trial lawyers. In fact, most lawyers' work involves planning -- for example, wills and trusts, real estate deals, and business mergers and acquisitions. Certain planning issues, such as the use of underspecified, or "open-textured" rules, are illustrated especially clearly in this domain. In this thesis, I set forth the characteristic features of planning in law, place it in the context of past artificial intelligence work in both law and planning, and describe CHIRON, a system that I have developed implementing my theory of open-textured planning in the domain of personal income tax law.

Case-based design promises important advantages over rule-based design systems. However, the actual implementation of the paradigm poses many problems which put the advantages into question. In our work on CADRE, a case-based building design system, we have encountered seven fundamental problems which we think are common to most case-based design systems. We describe the problems and the ways we either solved or worked around them in the CADRE system. This leads us to conclusions about the general applicability of case-based reasoning to building design.

This paper looks at EBMT from the perspective of the Case-based Reasoning (CBR) paradigm. We attempt to describe the task of machine translation (MT) seen as a potential application of CBR, and attempt to describe MT in standard CBR terms. The aim is to see if other applications of CBR can suggest better ways to approach EBMT.

The thesis: generic formal modelling frameworks can be used to encapsulate knowledge about human computer interaction with a particular class of system, namely interactive case memories (ICMs). A generic modelling framework can be used to ensure that ICMs developed exhibit desirable interaction properties, and can be re-used for the development of multiple systems. Some formal modelling frameworks that have been advocated to support the development of interactive systems have aimed to model a very wide class of systems at a highly abstract level. These frameworks are limited in their ability to express important properties that apply to particular systems, and may be open to multiple interpretations when applied to individual systems. Other frameworks have emphasised the specification of individual systems. Such single specifications provide limited re-usability. In this thesis I develop a generic framework to support the development of ICMs. To develop the framework I propose an abstr...

This tutorial article introduces the concepts and applications of Case-based Reasoning (CBR) systems. The first section briefly describes what is CBR, when to use CBR and why use CBR. The second section looks at the description and indexing of cases in CBR systems. The retrieval and adaptation processes for finding solutions are outlined in section three. Learning and maintenance of CBR, due to the changes in domain knowledge and task environments over time, are given in section four. The role of soft computing in CBR is briefly described in section five. The final section gives some examples of successful CBR applications in different areas. 1 What is Case-Based Reasoning? 1.1

In recent years, there has been a growing focus on research and applications that integrate several reasoning techniques. The general motivation for integrating several reasoning modes is to achieve a synergy which produces results that could not be obtained if each mode were operating individually. One such integration that has begun to see its application in many different problem domains is the integration of Constraint Satisfaction Problems (CSP) with Case-Based Reasoning (CBR). In this paper, we survey the various applications that have combined CSP and CBR. This exploration provides insight into how CSP can be enhanced by combining it with CBR, thereby enabling its usage in an even broader spectrum of applications. 1. INTRODUCTION In recent years, there has been a growing focus on research and applications that integrate several reasoning techniques [29,30]. The general motivation for integrating several reasoning modes is to achieve a synergy which produces results that could n...

Representing Physical and Design Knowledge in Innovative Design Nikitas Marinos Sgouros The ability to design is one of the hallmarks of intelligent behavior, since it allows an agent to shape its environment according to its needs. Therefore developing computational models of design should be one of the primary goals for a discipline such as Artificial Intelligence that aims to create intelligent artifacts. This thesis describes DIAS, a computational framework for innovative engineering design. This framework provides ways for representing the physical and design knowledge in a domain, along with methods for allowing these different types of knowledge to interact during the design process. This model has been instantiated in OUZO, a program that designs separation systems in chemical engineering. iii To my family iv ACKNOWLEDGEMENTS I would like to thank: ffl My advisor, Kenneth Forbus, for all the support and direction during this research. ffl The members of my committee, Lar...

MDA-903-90-K-0112. The Institute for the Learning Sciences was established in 1989 with Case-based reasoning is the technique of solving new problems by adapting solutions that were used to solve old problems. This reliance on previous experiences (or cases) is a hallmark of case-based reasoning. Each case can contain a great deal of information including a description of the situation that was encountered, ways in which the situation di ered from similar situations, and how the system reacted to the situation. In this report we trace the development of the case-based reasoning (CBR) paradigm and discuss in more detail the advantages of CBR as a problem-solving methodology. We then describe the general CBR algorithm and some of the fundamental issues that must be dealt with in any CBR system. Next, we present a survey of CBR systems that have been built to perform various tasks along with pointers for further reading. Finally, we conclude with a short discussion of the implications of CBR as a cognitive model and some pointers on how to go about building a CBR system. Contents i Case-Based Reasoning 1 1