An Integrated Analogy Model for Creative Reasoning

Analogical reasoning is a ubiquitous process playing a pivotal role in many disparate cognitive processes from induction, through metaphor interpretation, to creativity. We examine the role of analogy in creative reasoning highlighting the many similarities between both reasoning mechanisms. We interpret creativity as the search for some source analogue with which to reinterpret a given target domain. Such a mapping has the attractive quality that it explains anomalies in the current target interpretation. We have chosen as a basis for a detailed examination, creativity within the science domain as we feel that this offers the best opportunity for computational modelling

Searching for the Semantic Internet

Search engines, directories and web browsers all deal with the Internet at the level of individual web-pages. We argue that this is too low a level of resolution for many, including the non-casual surfer, who has detailed knowledge of his/her topic of interest. We present the shopping-mall metaphor that is based on identifying tightly integrated communities of web pages, where pages procure information from each other via hyperlinks. A search operation identifies these web-page communities, rather that individual web-pages, and the communities are visualised as a Virtual Reality shopping mall - for presentation on a VRML enabled web browser. Each information outlet (shop) can contain multiple information “products” (pages) gathered around a common theme. The metaphor serves to integrate both search and visualisation phases, presenting a coherent information collection to the user - regardless of the search domain

Investigating the Influence of Population and Generation Size on GeneRepair Templates

In 2005 Lolle et al published controversial findings showing that the Arabidopsis thaliana plant repairs invalid genetic information using the grandparent as a kind of repair template. We have previously shown how a genetic repair operator (GeneRepair) can be used to correct invalid individuals in an evolutionary strategy. It has been shown that superior results are produced when the individual’s grandparent is used as the repair template in comparison to using the individual’s parent. This paper investigates whether the results produced by GeneRepair templates are affected by parameters of population size and number of generations. The results indicate that the grandparent template outperforms the parent template regardless of population or generation size. These findings further supports the controversial theory of Lolle et al

Arabidopsis thaliana Inspired Genetic Restoration Strategies

A controversial genetic restoration mechanism has been proposed for the model organism Arabidopsis thaliana. This theory proposes that genetic material from non-parental ancestors is used to restore genetic information that was inadvertently corrupted during reproduction. We evaluate the effectiveness of this strategy by adapting it to an evolutionary algorithm solving two distinct benchmark optimization problems. We compare the performance of the proposed strategy with a number of alternate strategies – including the Mendelian alternative. Included in this comparison are a number of biologically implausible templates that help elucidate likely reasons for the relative performance of the different templates. Results show that the proposed non- Mendelian restoration strategy is highly effective across the range of conditions investigated – significantly outperforming the Mendelian alternative in almost every situation

Biologically Inspired Non-Mendelian Repair for Constraint Handling in Evolutionary Algorithms

This paper examines a repair technique that enables evolutionary algorithms to handle constraints. This repair technique, known as GeneRepair, repairs invalid individuals so that all problem constraints are met by every individual in the population. GeneRepair is based on the repair technique used by the Arabidopsis thaliana plant which was proposed by Lolle et al in 2005. This controversial repair method uses information inherited from ancestors previous to the parent (non-Mendelian inheritance) as a repair template to fix errors or invalidities in the current population. We compare the use of three different ancestors as repair templates and investigate the effects of various biological parameters on the choice of repair template to use

Generating a Topically Focused Virtual-Reality Internet

Surveys highlight that Internet users are frequently frustrated by failing to locate useful information, and by difficulty in browsing anarchically linked web-structures. We present a new Internet browsing application (called VR-net) that addresses these problems. It first identifies semantic domains consisting of tightly interconnected web-page groupings. The second part populates a 3D virtual world with these information sources, representing all relevant pages plus appropriate structural relations. Users can then easily browse through around a semantically focused virtual library

Features of Structure for Anaology Retrieval

Spontaneously retrieving analogies from presented problem data is an important phase of analogical reasoning, influencing many related cognitive processes. Existing models have focused on semantic similarity, but structural similarity is also a necessary requirement of any analogical comparison. We present a new technique for performing structure based analogy retrieval. This is founded upon derived attributes that explicitly encode elementary structural qualities of a domains representation. Crucially, these attributes are unrelated to the semantic content of the domain information, and encode only its structural qualities. We describe a number of derived attributes and detail the computation of the corresponding attribute values. We examine our models operation, detailing how it retrieves both semantically related and unrelated domains. We also present a comparison of our algorithms performance with existing models, using a structure rich but semantically impoverished domai

Searching for Serendipitous Analogies

Analogical reasoning is an acknowledged process behind many episodes of creativity. Typically, the creator chances upon information unrelated to the given problem – and solves the problem by analogy with this accidental source of inspiration. Current models of analogical retrieval do not explain how semantically unrelated source domains are retrieved. We present the RADAR algorithm that maps domains into a separate structure space, where domains with similar topological attributes are colocated. Each axis in structure space records the occurrence frequency of that feature in each domain. Nearest neighbour retrieval in structure space identifies structurally similar domains - from a diversity of semantic backgrounds. Structure based retrieval opens the possibility for creating an analogy model with far greater creativity potential than human reasoning

Effortful & Expert Evaluation in Developing Serious CST

This paper outlines some challenges involved in developing creativity support tools (CST) aimed at serious creativity. Such domains include: academic research, patent creation, literature-based discovery, creative ideation, etc. By referencing a common workflow model, we focus on the role of evaluation within the development cycle and finessing of a CST. Our focus lies in gathering expert evaluations by recognised leaders and critics whose opinions hold respect within that community. Such evaluations are typically; difficult to acquire, involves experts with very narrow field of expertise and necessitate detailed and complex evaluations. We outline an approach to evaluation that is based on pre-selected evaluators for whom personalised artefacts are created for evaluation