WorldCat Identities

De Wilde, Philippe 1958-

Overview
Works: 20 works in 93 publications in 1 language and 1,728 library holdings
Genres: Academic theses  Conference papers and proceedings 
Roles: Author, Collector, Editor, Other, htt
Classifications: QA76.87, 006.3
Publication Timeline
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Most widely held works by Philippe De Wilde
Convergence and knowledge processing in multi-agent systems by Maria Chli( )

20 editions published in 2009 in English and held by 490 WorldCat member libraries worldwide

"Multi-agent systems are complex systems comprised of multiple intelligent agents that act either independently or in cooperation with one another. Agent-based modelling is a method for studying complex systems like economies, societies, ecologies etc. Due to their complexity, very often mathematical analysis is limited in its ability to analyse such systems. In this case, agent-based modelling offers a practical, constructive method of analysis. The objective of this book is to shed light on some emergent properties of multi-agent systems. The authors focus their investigation on the effect of knowledge exchange on the convergence of complex, multi-agent systems."--Publisher's website
Neural network models : an analysis by Philippe De Wilde( )

20 editions published between 1995 and 1996 in English and held by 359 WorldCat member libraries worldwide

Providing a treatment of the main topics in neural networks, this volume focuses on multilayer networks and completely connected works, as well as discussing both analog and digital networks. The central themes are dynamical behaviour, attractors and capacity. Boltzmann machines are also discussed
Neural network models : theory and projects by Philippe De Wilde( Book )

17 editions published between 1996 and 1997 in English and held by 295 WorldCat member libraries worldwide

"Providing an in-depth treatment of neural network models, this volume explains and proves the main results in a clear and accessible way." "Topics covered include key concepts in neural networks, backpropagation, neurons in models of the brain, synchronous and discrete networks, differential mathematics, linear capacity, capacity from a signal to noise ratio, and neural networks and Markov chains." "Each chapter ends with a suggested project designed to help the reader develop an integrated knowledge of the theory, placing it within a practical application domain." "Neural Network Models: Theory and Projects concentrates on the essential parameters and results that will enable the reader to design hardware or software implementations of neural networks and to assess critically existing commercial products. It is suitable for final year, postgraduate and doctoral students in engineering, computing, applied mathematics, physics and biomedical systems, and will also be of interest to those working in science and industry who wish to obtain a firm grounding in the subject."--BOOK JACKET
2012 12th UK Workshop on Computational Intelligence (UKCI) : Heriot-Watt University, Edinburgh, UK, 5-7 September 2012 by UKCI (Atelier)( )

2 editions published in 2012 in English and held by 241 WorldCat member libraries worldwide

Practical applications of computational intelligence techniques by H.-J Zimmermann( Book )

11 editions published between 2001 and 2012 in English and held by 141 WorldCat member libraries worldwide

Computational intelligence paradigms have attracted the growing interest of researchers, scientists, engineers and application engineers in a number of everyday applications. These applications are not limited to any particular field and include engineering, business, banking and consumer electronics. Computational intelligence paradigms include artificial intelligence, artificial neural networks, fuzzy systems and evolutionary computing. Artificial neural networks can mimic the biological information processing mechanism in a very limited sense. Evolutionary computing algorithms are used for optimisation applications, and fuzzy logic provides a basis for representing uncertain and imprecise knowledge. Practical Applications of Computational Intelligence Techniques contains twelve chapters providing actual application of these techniques in the real world. Such examples include, but are not limited to, intelligent household appliances, aerial spray models, industrial applications and medical diagnostics and practice. This book will be useful to researchers, practicing engineers/scientists and students, who are interested in developing practical applications in a computational intelligence environment
Practical Applications of Computational Intelligence Techniques by Lakhmi Jain( )

1 edition published in 2001 in English and held by 73 WorldCat member libraries worldwide

Computational intelligence paradigms have attracted the growing interest of researchers, scientists, engineers and application engineers in a number of everyday applications. These applications are not limited to any particular field and include engineering, business, banking and consumer electronics. Computational intelligence paradigms include artificial intelligence, artificial neural networks, fuzzy systems and evolutionary computing. Artificial neural networks can mimic the biological information processing mechanism in a very limited sense. Evolutionary computing algorithms are used for optimisation applications, and fuzzy logic provides a basis for representing uncertain and imprecise knowledge.<br/> Practical Applications of Computational Intelligence Techniques contains twelve chapters providing actual application of these techniques in the real world. Such examples include, but are not limited to, intelligent household appliances, aerial spray models, industrial applications and medical diagnostics and practice. This book will be useful to researchers, practicing engineers/scientists and students, who are interested in developing practical applications in a computational intelligence environment
Convergence and Knowledge Processing in Multi-Agent Systems by Lakhmi Jain( Book )

7 editions published in 2009 in English and held by 38 WorldCat member libraries worldwide

Multi-agent systems are complex systems comprised of multiple intelligent agents that act either independently or in cooperation with one another. Agent-based modelling is a method for studying complex systems like economies, societies, ecologies etc. Due to their complexity, very often mathematical analysis is limited in its ability to analyse such systems. In this case, agent-based modelling offers a practical, constructive method of analysis. The objective of this book is to shed light on some emergent properties of multi-agent systems. The authors focus their investigation on the effect of knowledge exchange on the convergence of complex, multi-agent systems
Neural network models : an analysis by Philippe De Wilde( )

1 edition published in 2005 in English and held by 30 WorldCat member libraries worldwide

Practical Applications of Computational Intelligence Techniques( )

in English and held by 18 WorldCat member libraries worldwide

12th UK Workshop on Computational Intelligence (UKCI), 2012 5-7 Sept. 2012, Heriot-Watt University, Edinburgh, United Kingdom( )

1 edition published in 2012 in English and held by 17 WorldCat member libraries worldwide

Convergence and Knowledge Processing in Multi-Agent Systems by Lakhmi Jain( )

1 edition published in 2009 in Undetermined and held by 7 WorldCat member libraries worldwide

International Symposium on Mathematical Theory of Networks and Systems : July 3-6, 1979 by 1979, Delft) International Symposium on Mathematical Theory of Networks and Systems (3( Book )

1 edition published in 1979 in English and held by 2 WorldCat member libraries worldwide

Neural Network Models An Analysis by Philippe De Wilde( Book )

1 edition published in 1996 in English and held by 1 WorldCat member library worldwide

Providing an in-depth treatment of the main topics in neural networks this volume concentrates on multilayer networks and completely connected networks, as well as discussing both analog and digital networks. The central themes are dynamical behaviour, attractors and capacity. Boltzmann machines are also discussed. The subject is developed from scratch and does not use statistical physics. Because the volume adopts a pedagogical approach, explaining all steps in full, the style which the book takes it will appeal to engineers, computer scientists and applied mathematicians. The reader will learn the parameters and results that are most important for the design of neural networks and will be able to critically assess the existing commercial products or design a hardware or software implementation for him- or herself
Integrated circuit design book : papers on the VLSI design methodology from the ICD NELSIS Project( Book )

1 edition published in 1986 in English and held by 1 WorldCat member library worldwide

Neural Networks Models by Philippe De Wilde( Book )

2 editions published between 1996 and 1997 in English and held by 1 WorldCat member library worldwide

2012 12th UK Workshop on Computational Intelligence (UKCI 2012) Edinburgh, United Kingdom, 5-7 September 2012( Book )

1 edition published in 2012 in English and held by 1 WorldCat member library worldwide

Covergence and Knowledge Processing in Multi-agent Systems (Advanced information and knowledge processing) by Maria Chli( )

1 edition published in 2009 in Undetermined and held by 1 WorldCat member library worldwide

Fuzzy decision making system and the dynamics of business games by Festus Oderanti( )

1 edition published in 2011 in English and held by 1 WorldCat member library worldwide

Effective and efficient strategic decision making is the backbone for the success of a business organisation among its competitors in a particular industry. The results of these decision making processes determine whether the business will continue to survive or not. In this thesis, fuzzy logic (FL) concepts and game theory are being used to model strategic decision making processes in business organisations. We generally modelled competition by business organisations in industries as games where each business organization is a player. A player formulates his own decisions by making strategic moves based on uncertain information he has gained about the opponents. This information relates to prevailing market demand, cost of production, marketing, consolidation efforts and other business variables. This uncertain information is being modelled using the concept of fuzzy logic. In this thesis, simulation experiments were run and results obtained in six different settings. The first experiment addresses the payoff of the fuzzy player in a typical duopoly system. The second analyses payoff in an n-player game which was used to model a perfect market competition with many players. It is an extension of the two-player game of a duopoly market which we considered in the first experiment. The third experiment used and analysed real data of companies in a case study. Here, we chose the competition between Coca-cola and PepsiCo companies who are major players in the beverage industry. Data were extracted from their published financial statements to validate our experiment. In the fourth experiment, we modelled competition in business networks with uncertain information and varying level of connectivity. We varied the level of interconnections (connectivity) among business units in the business networks and investigated how missing links affect the payoffs of players on the networks. We used the fifth experiment to model business competition as games on boards with possible constraints or restrictions and varying level of connectivity on the boards. We also investigated this for games with uncertain information. We varied the level of interconnections (connectivity) among the nodes on the boards and investigated how these a ect the payoffs of players that played on the boards. We principally used these experiments to investigate how the level of availability of vital infrastructures (such as road networks) in a particular location or region affects profitability of businesses in that particular region. The sixth experiment contains simulations in which we introduced the fuzzy game approach to wage negotiation in managing employers and employees (unions) relationships. The scheme proposes how employers and employees (unions) can successfully manage the deadlocks that usually accompany wage negotiations. In all cases, fuzzy rules are constructed that symbolise various rules and strategic variables that firms take into consideration before taken decisions. The models also include learning procedures that enable the agents to optimize these fuzzy rules and their decision processes. This is the main contribution of the thesis: a set of fuzzy models that include learning, and can be used to improve decision making in business
 
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Convergence and knowledge processing in multi-agent systems Convergence and Knowledge Processing in Multi-Agent Systems
Covers
Neural network models : theory and projectsPractical applications of computational intelligence techniquesPractical Applications of Computational Intelligence TechniquesConvergence and Knowledge Processing in Multi-Agent SystemsNeural Networks Models
Alternative Names
DeWilde, Philippe 1958-

P De Wilde wetenschapper

Wilde Philippe de

Wilde, Philippe de 1958-

Languages
English (91)