12511763
Modelling Divergent Production: A multi-domain approach
1 Departamento de Engenharia Informática Universidade de Coimbra Abstract This paper presents an ongoing Ph.D. work on the area of Cognitive Modelling and, more specifically, about computational applications of theories of creativity. Without making claims to psychological views or results related to the mentioned theories, this work is concerned with a search for “different” solutions in a heterogeneous knowledge base composed of structures from a variety of domains. These structures and work upon them, in addition to a computational model of creative production, which is derived from the theory of divergent production [4], form the basis of this work. Its first applicational goal is to implement a system that generates musical ideas recurring to high-level abstractions from other domains (visual arts, story plots, architecture). Part of this has already been implemented and first results obtained. The overall architecture is described in the present paper.
9759378
Noun Sense Disambiguation with WordNet for Software Design Retrieval
Natural language understanding can be used to improve the usability of intelligent Computer Aided Software Engineering (CASE) tools. For a software designer it can be helpful in two ways: a broad range of natural language terms in the naming of software objects, attributes and methods can be used; and the system is able to understand the meaning of these terms so that it could use them in reasoning mechanisms like information retrieval. But, the problem of word sense disambiguation is an obstacle to the development of computational systems that can fully understand natural language. In order to deal with this problem, this paper presents a word sense disambiguation method and how it is integrated with a CASE tool.
11245975
Experiments with free concept generation in Divago
This paper presents a set of experiments we carried out with, Divago, a system that is an attempt to implement our ideas towards a computational model of creativity. It is expected to be able to generate novel concepts out of previous knowledge. Here we show its behaviour with a large dataset constructed independently by other researchers consisting of over 170 nouns (for a project named C^3). Each noun is represented with a syntax that is equivalent to the one adopted for Divago. We apply a two step experimentation procedure, which starts by ''training'' the system with ''preferred outcomes'' and then allowing it to do free generation, constrained by the pragmatic goal of a given query. We evaluate the results and make a short discussion regarding well-defined criteria of novelty and usefulness. We also present a comparison with a similar experiment done with C^3.
5517190
A Model for Creativity in Creature Generation
This paper brings a proposal and general specification of a new project that aims to apply Conceptual Blending (Fauconnier and Turner 1998) as a process of creature generation in games. The project we describe is based on Divago (Pereira and Cardoso, 2003 and should be able to bring novelty among creatures that populate a game. Moreover, it is expected to extend these capabilities to other objects in a game, towards a very dynamic environment. Since this is a work in progress, we provide the first preliminary results or experimental examples and try to provide the reader with a clear image of the framework to be followed.
15250271
Evaluation of Case-Based Maintenance Strategies in Software Design
CBR applications running in real domains can easily reach thousands of cases, which are stored in the case library. Retrieval times can increase greatly if the retrieval algorithm can not cope with such an amount of cases. Redundancy can also be a problem, focusing retrieval alternatives in a very restricted search space. Basically, the system's performance starts to degrade with the increase of the case-base size. Case-base maintenance allows CBR systems to deal with this problem, mainly through the use of case selection criteria. In this paper we present an experimental study about several case-base maintenance policies developed till now. We adapted and implemented these policies to a CBR system for software reuse and design, testing the applicability of these policies to cases with a complex representation (combination of tree and graph representations).
11166519
Case Retrieval of Software Designs using WordNet
Software design is one of the most important phases in system development, due to crucial decisions that are made during this phase. The need for software being developed in less time puts a lot of pressure in the design phase. One way to solve this problem is to reuse previous design solutions. In software design reuse the retrieval of relevant designs is a key issue. 
 
Case-Based Reasoning reuses past experiences to solve new problems, providing a reasoning framework for design reuse. But designing software involves reasoning at a more abstract level than coding software, thus a software design reuse tool must be able to work with a broad range of abstract concepts. A possible solution is the use of a common sense ontology, capable of providing this kind of knowledge, otherwise the system would have to demand a lot of knowledge from the designer. 
 
This paper presents an approach to software design retrieval based on Case-Based Reasoning combined with a common sense ontology - WordNet. We describe the case retrieval algorithm, the case similarity metrics and experimental results.
42460508
Probabilistic Evolution and the Busy Beaver Problem
8238424
GVR: A New Genetic Representation for the Vehicle Routing Problem
In this paper we analyse a new evolutionary approach to the vehicle routing problem. We present Genetic Vehicle Representation (GVR), a two-level representational scheme designed to deal in an effective way with all the information that candidate solutions must encode. Experimental results show that this method is both effective and robust, allowing the discovery of new best solutions for some well-known benchmarks.
10111787
Golomb Rulers: The Advantage of Evolution
In this paper we present a new evolutionary algorithm designed to efficiently search for optimal Golomb rulers. The proposed approach uses a redundant random keys representation to codify the information contained in a chromosome and relies on a simple interpretation algorithm to obtain feasible solutions. Experimental results show that this method is successful in quickly identifying good solutions and that can be considered as a realistic alternative to massive parallel approaches that need several months or years to discover high quality Golomb rulers.
35936505
Finding Manufacturing Expertise Using Ontologies and Cooperative Agents
The new product development process, in its early phases, congregates knowledge from diverse domains and sources, spread among specialists that usually are not aware of each other’s research interests. This work presents a tool designed to make the establishment of new communities or teams easier. The tool organizes their informal vocabulary into formal domain categories, in order to correlate them, and advises its users of potential networks they could belong to. An approach based on ontologies and machine learning is used to structure and make knowledge acquisition / retrieval, together with agents that cooperate and coordinate the access to the knowledge. The tool automatically updates its knowledge base relieving the user from tasks she/he is unfamiliar with. Initial experiments demonstrated the potential of this kind of tool. A test case is being developed encompassing members of a scientific network in the manufacturing area. Results will be analyzed envisaging its broader use and application to different knowledge domains.
6376797
Sharing engineering information and knowledge
This paper describes an agent-based recommendation system developed to support knowledge acquisition and sharing processes. Its purpose is to aid the process of community building, specially in the early phase of peer search and recognition in a distributed engineering environment, where multidisciplinary teams must be established. In this kind of problem information about possible candidates to make up the teams must be gathered from all available channels, including the electronic ones. Due to privacy issues, Web based data mining systems are not efficient for the purpose of constructing candidate's profiles, even if they can offer some help; therefore a distributed solution that permits each candidate's workplace to be explored was developed. As a means of aggregating collected knowledge for sharing, a conceptual model, relating candidate's profiles and their knowledge domain was developed in the form of an ontology. This strategy allows the system to be specialised in terms of the candidates' main knowledge domain.