Above are papers related to the following paper: [Paper_ID] Paper #73972. 	[Title] Improving Competence by Integrating Case-Based Reasoning and Heuristic Search [Abstract] We analyse the behaviour of a Propose & Revise architecture in the VT elevator design problem and we show that this problem solving method cannot solve all possible cases covered by the available domain knowledge. We investigate this problem and we show that this limitation is caused by the restricted search regime employed by the method and that the competence of the method cannot be improved by acquiring additional domain knowledge. We therefore propose an alternative design problem solver, which integrates case-based reasoning and heuristic search techniques and overcomes the competence-related limitations exhibited by the Propose & Revise architecture, while maintaining the same level of efficiency. We describe four algorithms for case-based design, which exploit both general properties of parametric design tasks and application specific heuristic knowledge. Please summarise all the given information.

Above are papers related to the following paper: [Paper_ID] Paper #50980. 	[Title] Parametric Design Problem Solving [Abstract] The aim of this paper is to understand what is involved in parametric design problem solving. In order to achieve this goal, in this paper i) we identify and detail the conceptual elements defining a parametric design task specification; ii) we illustrate how these elements are interpreted and operationalised during the design process; and iii) we formulate a generic model of parametric design problem solving. We then redescribe a number of problem solving methods in terms of the proposed generic model and we show that such a redescription enables us to provide a more precise account of the different competence behaviours expressed by the methods in Design is about constructing artifacts. This means that, broadly speaking, any design process is 'creative', in the sense that a design process produces a 'new solution', as opposed to selecting a solution from a predefined set. While recognizing the essential creative elements present in any design process, researchers, e.g. Gero (1990), restrict the use of the term 'creative design' to those design applications where the design elements of the target artifact cannot be selected from a predefined set. For instance, when designing a new car model it is normally the case that some design innovations are included, which were not present in previous car designs. In other words it is not (always) possible to characterise the process of designing a new car as one in which components are assembled and configured from a predefined set. Nevertheless, in a large number of real-world applications it is possible to assume that the target artifact is going to be designed in terms of predefined design elements. In such a scenario the design process consists of assembling and configuring these preexisting design elements in a way which satisfies the design requirements and constraints, and approximates some, typically cost-related, optimization criterion. This class of design tasks takes the name of configuration design (Stefik, 1995). In many cases, typically when the problem in hand does not exhibit complex spatial requirements and all possible solutions adhere to a common solution template, it is possible to simplify the configuration design problem even further, by modelling the target artifact as a set of parameters and characterizing design problem solving as the process of assigning values to parameters in accordance with the given design requirements, constraints, and optimization criterion. When this assumption is true for a particular task, we say that this is a parametric design task. The VT application (Marcus et al., 1988; Yost and Rothenfluh, 1996) provides a well-known example of a parametric design task. The aim of this paper is to understand what is involved in parametric design problem solving. In order to achieve this goal, in this paper i) we identify and detail the conceptual elements defining a parametric design task specification; ii) we illustrate how these elements are interpreted and operationalised during the design process; and iii) we produce a generic model of parametric design problem solving, characterised at the knowledge level, which generalizes from existing methods for parametric design. We then redescribe a number of problem solving methods in terms of the question. Please summarise all the given information.

Paper #73972 has the title `Improving Competence by Integrating Case-Based Reasoning and Heuristic Search  
` and the abstract `We analyse the behaviour of a Propose & Revise architecture in the VT elevator design problem and we show that this problem solving method cannot solve all possible cases covered by the available domain knowledge. We investigate this problem and we show that this limitation is caused by the restricted search regime employed by the method and that the competence of the method cannot be improved by acquiring additional domain knowledge. We therefore propose an alternative design problem solver, which integrates case-based reasoning and heuristic search techniques and overcomes the competence-related limitations exhibited by the Propose & Revise architecture, while maintaining the same level of efficiency. We describe four algorithms for case-based design, which exploit both general properties of parametric design tasks and application specific heuristic knowledge.
`.
Question: Which category should Paper #73972 be classified as ?
You can select one from ['Neural_Networks', 'Case_Based', 'Theory', 'Reinforcement_Learning', 'Probabilistic_Methods', 'Rule_Learning', 'Genetic_Algorithms'].


Paper #73972 has the title `Improving Competence by Integrating Case-Based Reasoning and Heuristic Search  
` and the abstract `We analyse the behaviour of a Propose & Revise architecture in the VT elevator design problem and we show that this problem solving method cannot solve all possible cases covered by the available domain knowledge. We investigate this problem and we show that this limitation is caused by the restricted search regime employed by the method and that the competence of the method cannot be improved by acquiring additional domain knowledge. We therefore propose an alternative design problem solver, which integrates case-based reasoning and heuristic search techniques and overcomes the competence-related limitations exhibited by the Propose & Revise architecture, while maintaining the same level of efficiency. We describe four algorithms for case-based design, which exploit both general properties of parametric design tasks and application specific heuristic knowledge.
`.
Question: Which category should Paper #73972 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