Above are papers related to the following paper: [Paper_ID] Paper #74975. 	[Title] Towards More Creative Case-Based Design Systems [Abstract] Case-based reasoning (CBR) has a great deal to offer in supporting creative design, particularly processes that rely heavily on previous design experience, such as framing the problem and evaluating design alternatives. However, most existing CBR systems are not living up to their potential. They tend to adapt and reuse old solutions in routine ways, producing robust but uninspired results. Little research effort has been directed towards the kinds of situation assessment, evaluation, and assimilation processes that facilitate the exploration of ideas and the elaboration and redefinition of problems that are crucial to creative design. Also, their typically rigid control structures do not facilitate the kinds of strategic control and opportunism inherent in creative reasoning. In this paper, we describe the types of behavior we would like case-based design systems to support, based on a study of designers working on a mechanical engineering problem. We show how the standard CBR framework should be extended and we describe an architecture we are developing to experiment with these ideas. 1 Please summarise all the given information.

Above are papers related to the following paper: [Paper_ID] Paper #1107041. 	[Title] Developing Case-Based Reasoning for Structural Design [Abstract] The use of case-based reasoning as a process model of design involves the subtasks of recalling previously known designs from memory and adapting these design cases or subcases to fit the current design context. The development of this process model for a particular design domain proceeds in parallel with the development of a representation for the cases, the case memory organisation, and the design knowledge needed in addition to specific designs. The selection of a particular representational paradigm for these types of information, and the details of its use for a particular problemsolving domain, depend on the intended use of the information to be represented and the project information available, as well as the nature of the domain. In this paper we describe the development and implementation of four case-based design systems: CASECAD, CADSYN, WIN, and DEMEX. Each system is described in terms of the content, organisation, and source of case memory, and the implementation of case recall and case adaptation. A comparison of these systems considers the relative advantages and disadvantages of the implementations. Please summarise all the given information.

Above are papers related to the following paper: [Paper_ID] Paper #1107010. 	[Title] an Opportunistic Enterprise [Abstract] Tech Report GIT-COGSCI-97/04 Abstract This paper identifies goal handling processes that begin to account for the kind of processes involved in invention. We identify new kinds of goals with special properties and mechanisms for processing such goals, as well as means of integrating opportunism, deliberation, and social interaction into goal/plan processes. We focus on invention goals, which address significant enterprises associated with an inventor. Invention goals represent seed goals of an expert, around which the whole knowledge of an expert gets reorganized and grows more or less opportunistically. Invention goals reflect the idiosyncrasy of thematic goals among experts. They constantly increase the sensitivity of individuals for particular events that might contribute to their satisfaction. Our exploration is based on a well-documented example: the invention of the telephone by Alexander Graham Bell. We propose mechanisms to explain: (1) how Bell's early thematic goals gave rise to the new goals to invent the multiple telegraph and the telephone, and (2) how the new goals interacted opportunistically. Finally, we describe our computational model, ALEC, that accounts for the role of goals in invention. Please summarise all the given information.

Above are papers related to the following paper: [Paper_ID] Paper #936. 	[Title] The Use of Explicit Goals for Knowledge to Guide Inference and Learning [Abstract] Combinatorial explosion of inferences has always been a central problem in artificial intelligence. Although the inferences that can be drawn from a reasoner's knowledge and from available inputs is very large (potentially infinite), the inferential resources available to any reasoning system are limited. With limited inferential capacity and very many potential inferences, reasoners must somehow control the process of inference. Not all inferences are equally useful to a given reasoning system. Any reasoning system that has goals (or any form of a utility function) and acts based on its beliefs indirectly assigns utility to its beliefs. Given limits on the process of inference, and variation in the utility of inferences, it is clear that a reasoner ought to draw the inferences that will be most valuable to it. This paper presents an approach to this problem that makes the utility of a (potential) belief an explicit part of the inference process. The method is to generate explicit desires for knowledge. The question of focus of attention is thereby transformed into two related problems: How can explicit desires for knowledge be used to control inference and facilitate resource-constrained goal pursuit in general? and, Where do these desires for knowledge come from? We present a theory of knowledge goals, or desires for knowledge, and their use in the processes of understanding and learning. The theory is illustrated using two case studies, a natural language understanding program that learns by reading novel or unusual newspaper stories, and a differential diagnosis program that improves its accuracy with experience. Please summarise all the given information.

Above are papers related to the following paper: [Paper_ID] Paper #38845. 	[Title] Opportunistic Reasoning: A Design Perspective [Abstract] An essential component of opportunistic behavior is opportunity recognition, the recognition of those conditions that facilitate the pursuit of some suspended goal. Opportunity recognition is a special case of situation assessment, the process of sizing up a novel situation. The ability to recognize opportunities for reinstating suspended problem contexts (one way in which goals manifest themselves in design) is crucial to creative design. In order to deal with real world opportunity recognition, we attribute limited inferential power to relevant suspended goals. We propose that goals suspended in the working memory monitor the internal (hidden) representations of the currently recognized objects. A suspended goal is satisfied when the current internal representation and a suspended goal match. We propose a computational model for working memory and we compare it with other relevant theories of opportunistic planning. This working memory model is implemented as part of our IMPROVISER system. Please summarise all the given information.

Above are papers related to the following paper: [Paper_ID] Paper #22386. 	[Title] CASE-BASED CREATIVE DESIGN [Abstract] Designers across a variety of domains engage in many of the same creative activities. Since much creativity stems from using old solutions in novel ways, we believe that case-based reasoning can be used to explain many creative design processes. Please summarise all the given information.

Above are papers related to the following paper: [Paper_ID] Paper #5075. 	[Title] An Investigation of Marker-Passing Algorithms for Analogue Retrieval [Abstract] If analogy and case-based reasoning systems are to scale up to very large case bases, it is important to analyze the various methods used for retrieving analogues to identify the features of the problem for which they are appropriate. This paper reports on one such analysis, a comparison of retrieval by marker passing or spreading activation in a semantic network with Knowledge-Directed Spreading Activation, a method developed to be well-suited for retrieving semantically distant analogues from a large knowledge base. The analysis has two complementary components: (1) a theoretical model of the retrieval time based on a number of problem characteristics, and (2) experiments showing how the retrieval time of the approaches varies with the knowledge base size. These two components, taken together, suggest that KDSA is more likely than SA to be able to scale up to retrieval in large knowledge bases. Please summarise all the given information.

Above are papers related to the following paper: [Paper_ID] Paper #1110579. 	[Title] Modeling Invention by Analogy in ACT-R [Abstract] We investigate some aspects of cognition involved in invention, more precisely in the invention of the telephone by Alexander Graham Bell. We propose the use of the Structure-Behavior-Function (SBF) language for the representation of invention knowledge; we claim that because SBF has been shown to support a wide range of reasoning about physical devices, it constitutes a plausible account of how an inventor might represent knowledge of an invention. We further propose the use of the ACT-R architecture for the implementation of this model. ACT-R has been shown to very precisely model a wide range of human cognition. We draw upon the architecture for execution of productions and matching of declarative knowledge through spreading activation. Thus we present a model which combines the well-established cognitive validity of ACT-R with the powerful, specialized model-based reasoning methods facilitated by SBF. Please summarise all the given information.

Above are papers related to the following paper: [Paper_ID] Paper #1128407. 	[Title] Understanding Creativity: A Case-Based Approach [Abstract] Dissatisfaction with existing standard case-based reasoning (CBR) systems has prompted us to investigate how we can make these systems more creative and, more broadly, what would it mean for them to be more creative. This paper discusses three research goals: understanding creative processes better, investigating the role of cases and CBR in creative problem solving, and understanding the framework that supports this more interesting kind of case-based reasoning. In addition, it discusses methodological issues in the study of creativity and, in particular, the use of CBR as a research paradigm for exploring creativity. Please summarise all the given information.

Above are papers related to the following paper: [Paper_ID] Paper #3932. 	[Title] Finding Analogues for Innovative Design [Abstract] Knowledge Systems Laboratory March 1995 Report No. KSL 95-32 Please summarise all the given information.

Above are papers related to the following paper: [Paper_ID] Paper #100701. 	[Title] Design by Interactive Exploration Using Memory-Based Techniques [Abstract] One of the characteristics of design is that designers rely extensively on past experience in order to create new designs. Because of this, memory-based techniques from artificial intelligence, which help store, organise, retrieve, and reuse experiential knowledge held in memory, are good candidates for aiding designers. Another characteristic of design is the phenomenon of exploration in the early stages of design configuration. A designer begins with an ill-structured, partially defined, problem specification, and through a process of exploration gradually refines and modifies it as his/her understanding of the problem improves. In this paper we describe demex, an interactive computer-aided design system that employs memory-based techniques to help its users explore the design problems they pose to the system, in order to acquire a better understanding of the requirements of the problems. demex has been applied in the domain of structural design of buildings. Please summarise all the given information.

Above are papers related to the following paper: [Paper_ID] Paper #38846. 	[Title] Explaining Serendipitous Recognition in Design [Abstract] Creative designers often see solutions to pending design problems in the everyday objects surrounding them. This can often lead to innovation and insight, sometimes revealing new functions and purposes for common design pieces in the process. We are interested in modeling serendipitous recognition of solutions to pending problems in the context of creative mechanical design. This paper characterizes this ability, analyzing observations we have made of it, and placing it in the context of other forms of recognition. We propose a computational model to capture and explore serendipitous recognition which is based on ideas from reconstructive dynamic memory and situation assessment in case-based reasoning. Please summarise all the given information.

Paper #74975 has the title `Towards More Creative Case-Based Design Systems  
` and the abstract `Case-based reasoning (CBR) has a great deal to offer in supporting creative design, particularly processes that rely heavily on previous design experience, such as framing the problem and evaluating design alternatives. However, most existing CBR systems are not living up to their potential. They tend to adapt and reuse old solutions in routine ways, producing robust but uninspired results. Little research effort has been directed towards the kinds of situation assessment, evaluation, and assimilation processes that facilitate the exploration of ideas and the elaboration and redefinition of problems that are crucial to creative design. Also, their typically rigid control structures do not facilitate the kinds of strategic control and opportunism inherent in creative reasoning. In this paper, we describe the types of behavior we would like case-based design systems to support, based on a study of designers working on a mechanical engineering problem. We show how the standard CBR framework should be extended and we describe an architecture we are developing to experiment with these ideas. 1 
`.
Question: Which category should Paper #74975 be classified as ?
You can select one from ['Neural_Networks', 'Case_Based', 'Theory', 'Reinforcement_Learning', 'Probabilistic_Methods', 'Rule_Learning', 'Genetic_Algorithms'].


Paper #74975 has the title `Towards More Creative Case-Based Design Systems  
` and the abstract `Case-based reasoning (CBR) has a great deal to offer in supporting creative design, particularly processes that rely heavily on previous design experience, such as framing the problem and evaluating design alternatives. However, most existing CBR systems are not living up to their potential. They tend to adapt and reuse old solutions in routine ways, producing robust but uninspired results. Little research effort has been directed towards the kinds of situation assessment, evaluation, and assimilation processes that facilitate the exploration of ideas and the elaboration and redefinition of problems that are crucial to creative design. Also, their typically rigid control structures do not facilitate the kinds of strategic control and opportunism inherent in creative reasoning. In this paper, we describe the types of behavior we would like case-based design systems to support, based on a study of designers working on a mechanical engineering problem. We show how the standard CBR framework should be extended and we describe an architecture we are developing to experiment with these ideas. 1 
`.
Question: Which category should Paper #74975 be classified as ?
You can select one from ['Neural_Networks', 'Case_Based', 'Theory', 'Reinforcement_Learning', 'Probabilistic_Methods', 'Rule_Learning', 'Genetic_Algorithms'].

This paper should be classified into: Case_Based