11145016
Niching techniques: a study on the cluster geometry optimization problem
The cluster geometry optimization is one of these problems. The same cluster structure can be encoded in innumerable ways. A single translation or rotation performed in the cluster can lead to different genotypes for similar structures. A reliable similarity function can be computationally prohibitive or even impossible to define. We analyze the behavior of an alternative technique free of distance measures, the Spatially-Dispersed Genetic Algorithm [1] (sdGA), and its application on the cluster geometry optimization.
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.
2344862
Busy Beaver - The Influence of Representation
The Busy Beaver is an interesting theoretical problem proposed by Rado in 1962, in the context of the existence of non computable functions. In this paper we propose an evolutionary approach to this problem. We will focus on the representational issues, proposing alternative ways of codifying and interpreting Turing Machines, designed to take advantage of the existence of sets of equivalent Turing Machines. The experimental results show that these alternatives provide improvement over the "standard" genetic codification.
9947181
The Influence of Learning in the Evolution of Busy Beavers
The goal of this research is to study how individual learning interacts with an evolutionary algorithm in its search for good candidates for the Busy Beaver problem. Two learning models, designed to act as local search procedures, are proposed. Experimental results show that local search methods that are able to perform several modifications in the structure of an individual in each learning step provide an important advantage. Some insight about the role that evolution and learning play during search is also presented.
42460508
Probabilistic Evolution and the Busy Beaver Problem
12781827
On the influence of GVR in vehicle routing
A comparative study is made between a new evolutionary approach for the Vehicle Routing Problem (VRP) and a standard evolutionary model, based on Path Representation. Genetic Vehicle Representation (GVR) is the new two-level representational scheme designed to deal in an effective way with all the information needed by candidate solutions. Experimental results, obtained from a set of VRP instances, show performance improvements when GVR is used.
16874859
Linear Logic for Meaning Assembly
Semantic theories of natural language associate meanings with utterances by providing meanings for lexical items and rules for determining the meaning of larger units given the meanings of their parts. Meanings are often assumed to combine via function application, which works well when constituent structure trees are used to guide semantic composition. However, we believe that the functional structure of Lexical-Functional Grammar is best used to provide the syntactic information necessary for constraining derivations of meaning in a cross-linguistically uniform format. It has been difficult, however, to reconcile this approach with the combination of meanings by function application. In contrast to compositional approaches, we present a deductive approach to assembling meanings, based on reasoning with constraints, which meshes well with the unordered nature of information in the functional structure. Our use of linear logic as a `glue' for assembling meanings allows for a coherent treatment of the LFG requirements of completeness and coherence as well as of modification and quantification.
18854826
Case-Based Reuse of UML Diagrams
Software reuse has the potential of reducing development time and increasing software quality. There are several types of knowledge that can be reused, with code being the most common reused one. Code reuse is the most direct and easier type of reuse, but is not the most efficient one. Design reuse is more productive than code reuse, because changes at the design level can have big effects on the implementation level, thus compromising code reuse. This paper presents an approach to reuse of software designs, which are in the form of UML class diagrams. The presented approach is based on Case-Based Reasoning providing a framework for storing, retrieving, creating and revising class diagrams.
7441581
Quantifiers, Anaphora, and Intensionality
The relationship between Lexical-Functional Grammar (LFG) functional structures (f-structures) for sentences and their semanticinterpretations can be formalized in linear logic in a way thatcorrectly explains the observed interactions between quantifier scopeambiguity, bound anaphora and intensionality.Our linear-logic formalization of the compositional properties ofquantifying expressions in natural language obviates the need forspecial mechanisms, such as Cooper storage, in representing thescoping possibilities of quantifying expressions. Instead, thesemantic contribution of a quantifier is recorded as a linear-logicformula whose use in a proof will establish the scope of thequantifier. Different proofs can lead to different scopes. In eachcomplete proof, the properties of linear logic ensure thatquantifiers are properly scoped.The interactions between quantified NPs and intensional verbs such as’’seek‘‘ are also accounted for in this deductive setting. A singlespecification in linear logic of the argument requirements ofintensional verbs is sufficient to derive the correct readingpredictions for intensional-verb clauses both with nonquantified andwith quantified direct objects. In particular, both de dictoand de re readings are derived for quantified objects. Theeffects of type-raising or quantifying-in rules in other frameworksjust follow here as linear-logic theorems.While our approach resembles current categorial approaches inimportant ways (Moortgat, 1988, 1992a; Carpenter, 1993; Morrill, 1994)it differs from them in allowing the greater compositional flexibility ofcategorial semantics (van Benthem, 1991)while maintaining a precise connection to syntax. As a result, we areable to provide derivations for certain readings of sentences withintensional verbs and complex direct objects whose derivation inpurely categorial accounts of the syntax-semantics interface appearsto require otherwise unnecessary semantic decompositions of lexicalentries.
16219760
Selection and Reuse of Software Design Patterns Using CBR and WordNet
Software engineers and programmers deal with repeated problems and situations in the course of software design. This lead to the development of software design patterns, which can be defined as a description of an abstract solution for abstract design problems. Existing approaches to pattern application using computer tools, need the help and guidance of a human designer to select which design pattern to apply. The automation of this task opens the possibility of CASE design tools providing complete automation for the application of design patterns, and the offering new functionalities that can help the software designer to improve systems, and do better software reuse. In this paper we present an approach that automates design pattern selection and application. This approach is based on CaseBased Reasoning and WordNet, showing how they are combined to generate evolved software design diagrams. We also present an experimental study of our approach.
15139022
Darwinci: Creating Bridges to Creativity
This paper presents Darwinci, a system that generates new ideas, using a multi-domain knowledge base composed by musical and drawing structures. Its theoretical background comes from the theory of Divergent Production as stated in [7], Genetic Algorithms and metaphor interpretation. Rather than attempting to model human thought, Darwinci’s main goal is to make cross-domain transfer of ideas, in order to create something new, thus becoming a good proposal for creative problem solving.