Open Access
On Finding an Optimized Categorization in Conceptual Spaces using Genetic Algorithms
Mihai Horia,Zaharia Florin +1 more
TLDR
In this paper a genetic algorithm approach was used in order to obtain two major desired eects to increase the disjunction level in knowledge representation and the processing speed.Abstract:
The complex analyses required by artificial intelligence applications need both a flexible structure for information representation and a quick and ecient method for information categorization. The latter has a great impact on the former because it can increase or not the knowledge database dimension. This situation can sometimes lead to undesired complexity. In this paper a genetic algorithm approach was used in order to obtain two major desired eects. The first one is to increase the disjunction level in knowledge representation and the second is to increase the processing speed. Comparisons were made between our solutions and the weighting results of ReliefF algorithm.read more
Citations
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Journal ArticleDOI
A concept geometry for conceptual spaces
TL;DR: This paper generalizes and extends the theory of conceptual spaces as originally proposed by Gardenförs to provide further geometric representations of both concepts and object observations within a multi-dimensional fuzzy space corresponding to a subset of a unit hypercube.
Book ChapterDOI
Evolving equilibrium policies for a multiagent reinforcement learning problem with state attractors
TL;DR: A new benchmark problem is proposed, which involves the need for cooperation, competition and synchronization between agents, and the notion of state attractor is introduced, such that agents compute their actions based on the proximity of their current state to the nearest state attractsor.
References
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Book
Adaptation in natural and artificial systems
TL;DR: Names of founding work in the area of Adaptation and modiication, which aims to mimic biological optimization, and some (Non-GA) branches of AI.
Book
Genetic Algorithms + Data Structures = Evolution Programs
TL;DR: GAs and Evolution Programs for Various Discrete Problems, a Hierarchy of Evolution Programs and Heuristics, and Conclusions.
Journal ArticleDOI
An Introduction to Genetic Algorithms.
TL;DR: An Introduction to Genetic Algorithms as discussed by the authors is one of the rare examples of a book in which every single page is worth reading, and the author, Melanie Mitchell, manages to describe in depth many fascinating examples as well as important theoretical issues.
Book ChapterDOI
Estimating attributes: analysis and extensions of RELIEF
TL;DR: In the context of machine learning from examples this paper deals with the problem of estimating the quality of attributes with and without dependencies among them and is analysed and extended to deal with noisy, incomplete, and multi-class data sets.
Book
Conceptual Spaces: The Geometry of Thought
TL;DR: Peter Gardenfors's theory of conceptual spaces presents a framework for representing information on the conceptual level and shows how conceptual spaces can serve as an explanatory framework for a number of empirical theories, in particular those concerning concept formation, induction, and semantics.
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