43376763
An Artificial Life Model for Information Retrieval in a Distributed Environment
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.
8920330
On the Evolution of Evolutionary Algorithms
In this paper we discuss the evolution of several components of a traditional Evolutionary Algorithm, such as genotype to phenotype mappings and genetic operators, presenting a formalized description of how this can be attained. We then focus on the evolution of mapping functions, for which we present experimental results achieved with a meta-evolutionary scheme.
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.
18592363
Evolving Golomb Rulers
A Golomb Ruler is defined as a ruler that has marks unevenly spaced at integer locations in such a way that the distance between any two marks is unique. Unlike usual rulers, they have the ability to measure more discrete measures than the number of marks they possess. Although the definition of a Golomb Ruler does not place any restriction on the length of the ruler, researchers are usually interested in rulers with minimum length. An Optimal Golomb Ruler (OGR) is defined as the shortest length ruler for a given number of marks [1].
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.
1469013
Solution Verification in Software Design: A CBR Approach
Software design is becoming a demanding task, not only because the complexity of software systems is increasing, but also due to the pressure that development teams suffer from clients. CASE tools capable of performing more work and of having more intelligent abilities are needed, so that, they can provide more help to the designer. In this paper we describe a CASE tool capable of assisting the designer in a more intelligent way, be it by suggesting new solutions or by learning user preferences. We detail how the solutions are generated and focus on the verification process, which enables the new designs to have less errors. This verification process takes a CBR approach, which has the advantage of being personalized. We describe experimental results that show the effect of the verification process in the generated solutions.
11200577
Plans as Structured Networks of Hierarchically and Temporally Related Case Pieces
This paper describes a representation of plan cases as a structured set of goals and actions. These goals and actions are the unit pieces that form a case. These case pieces are related each other by hierarchical and temporal links (explanations) forming a tree-like network. We give importance not just to explicit links, i.e., links between case pieces which are concretely known, but also to implicit ones, i.e., possibly unknown links between case pieces. Each case piece is explained by antecedent links and explains other case pieces by consequent links. The retrieval of a case piece is mainly guided by its links and by its surrounding case pieces. Our concept of case piece usefulness is briefly explained. We discuss the benefit of reusing and directly accessing small case pieces from multiple cases for improving the Case-Based Reasoning (CBR) systems' capability and efficiency to solve problems. We explain the importance of stepwise refinement in plan cases and also the role that temporal representation can take in the meaningful and coherent construction of planning problem solutions.
5245012
A Conditional Random Field for Discriminatively-trained Finite-state String Edit Distance
The need to measure sequence similarity arises in information extraction, object identity, data mining, biological sequence analysis, and other domains. This paper presents discriminative string-edit CRFs, a finite-state conditional random field model for edit sequences between strings. Conditional random fields have advantages over generative approaches to this problem, such as pair HMMs or the work of Ristad and Yianilos, because as conditionally-trained methods, they enable the use of complex, arbitrary actions and features of the input strings. As in generative models, the training data does not have to specify the edit sequences between the given string pairs. Unlike generative models, however, our model is trained on both positive and negative instances of string pairs. We present positive experimental results on several data sets.
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.
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.