Evolution Re Algorithmen
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Computational Techniques for Modelling Learning in Economics
Author: Thomas Brenner
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-12-06
Computational Techniques for Modelling Learning in Economics offers a critical overview of the computational techniques that are frequently used for modelling learning in economics. It is a collection of papers, each of which focuses on a different way of modelling learning, including the techniques of evolutionary algorithms, genetic programming, neural networks, classifier systems, local interaction models, least squares learning, Bayesian learning, boundedly rational models and cognitive learning models. Each paper describes the technique it uses, gives an example of its applications, and discusses the advantages and disadvantages of the technique. Hence, the book offers some guidance in the field of modelling learning in computation economics. In addition, the material contains state-of-the-art applications of the learning models in economic contexts such as the learning of preference, the study of bidding behaviour, the development of expectations, the analysis of economic growth, the learning in the repeated prisoner's dilemma, and the changes of cognitive models during economic transition. The work even includes innovative ways of modelling learning that are not common in the literature, for example the study of the decomposition of task or the modelling of cognitive learning.
Data Driven e-Science
Author: Simon C. Lin
language: en
Publisher: Springer Science & Business Media
Release Date: 2011-02-04
ISGC 2010, The International Symposium on Grid Computing was held at Academia Sinica, Taipei, Taiwan, March, 2010. The 2010 symposium brought together prestigious scientists and engineers worldwide to exchange ideas, present challenges/solutions and to discuss new topics in the field of Grid Computing. Data Driven e-Science: Use Cases and Successful Applications of Distributed Computing Infrastructures (ISGC 2010), an edited volume, introduces the latest achievements in grid technology for Biomedicine Life Sciences, Middleware, Security, Networking, Digital Library, Cloud Computing and more. This book provides Grid developers and end users with invaluable information for developing grid technology and applications. The last section of this book presents future development in the field of Grid Computing. This book is designed for a professional audience composed of grid users, developers and researchers working in the field of grid computing. Advanced-level students focused on computer science and engineering will also find this book valuable as a reference or secondary text book.
Computational Collective Intelligence
This two-volume set (LNAI 11055 and LNAI 11056) constitutes the refereed proceedings of the 10th International Conference on Collective Intelligence, ICCCI 2018, held in Bristol, UK, in September 2018 The 98 full papers presented were carefully reviewed and selected from 240 submissions. The conference focuses on knowledge engineering and semantic web, social network analysis, recommendation methods and recommender systems, agents and multi-agent systems, text processing and information retrieval, data mining methods and applications, decision support and control systems, sensor networks and internet of things, as well as computer vision techniques.