The microelectronics market trends present an ever-increasing level of complexity with special emphasis on the production of complex mixed-signal systems-on-chip. Strict economic and design pressures have driven the d...
ISBN:
(数字)9783642123467
ISBN:
(纸本)9783642123450
The microelectronics market trends present an ever-increasing level of complexity with special emphasis on the production of complex mixed-signal systems-on-chip. Strict economic and design pressures have driven the development of new methods to automate the analog design process. However, and despite some significant research efforts, the essential act of design at the transistor level is still performed by the trial and error interaction between the designer and the simulator. This book presents a new design automation methodology based on a modified genetic algorithm kernel, in order to improve efficiency on the analog IC design cycle. The proposed approach combines a robust optimization with corner analysis, machine learning techniques and distributed processing capability able to deal with multi-objective and constrained optimization problems. The resulting optimization tool and the improvement in design productivity is demonstrated for the design of CMOS operational amplifiers.
During the last decade, the French-speaking scientific community developed a very strong research activity in the field of Knowledge Discovery and Management (KDM or EGC for Extraction et Gestion des Connaissances in ...
ISBN:
(数字)9783642005800
ISBN:
(纸本)9783642005794
During the last decade, the French-speaking scientific community developed a very strong research activity in the field of Knowledge Discovery and Management (KDM or EGC for Extraction et Gestion des Connaissances in French), which is concerned with, among others, Data Mining, Knowledge Discovery, Business intelligence, Knowledge Engineering and SemanticWeb. The recent and novel research contributions collected in this book are extended and reworked versions of a selection of the best papers that were originally presented in French at the EGC 2009 Conference held in Strasbourg, France on January 2009. The volume is organized in four parts. Part I includes five papers concerned by various aspects of supervised learning or information retrieval. Part II presents five papers concerned with unsupervised learning issues. Part III includes two papers on data streaming and two on security while in Part IV the last four papers are concerned with ontologies and semantic.
The objective in editing this book was to assemble a sample of the best work in parallel and distributed biologically inspired algorithms. The editors invited researchers in different domains to submit their work. The...
ISBN:
(数字)9783642106750
ISBN:
(纸本)9783642106743
The objective in editing this book was to assemble a sample of the best work in parallel and distributed biologically inspired algorithms. The editors invited researchers in different domains to submit their work. They aimed to include diverse topics to appeal to a wide audience. Some of the chapters summarize work that has been ongoing for several years, while others describe more recent exploratory work. Collectively, these works offer a global snapshot of the most recent efforts of bioinspired algorithms researchers aiming at profiting from parallel and distributed computer architecturesincluding GPUs, Clusters, Grids, volunteer computing and p2p networks as well as multi-core processors. This volume will be of value to a wide set of readers, including, but not limited to specialists in Bioinspired Algorithms, Parallel and Distributed Computing, as well as computer science students trying to figure out new paths towards the future of computationalintelligence.
The book consists of 32 extended chapters which have been based on selected submissions to the poster session organized during the 2nd Asian Conference on Intelligent Information and Database Systems (24-26 March 2010...
ISBN:
(数字)9783642120909
ISBN:
(纸本)9783642120893
The book consists of 32 extended chapters which have been based on selected submissions to the poster session organized during the 2nd Asian Conference on Intelligent Information and Database Systems (24-26 March 2010 in Hue, Vietnam). The book is organized into four parts devoted to information retrieval and management, service composition and user-centered approach, data mining and knowledge extraction, and computationalintelligence, respectively. All chapters in the book discuss theoretical and practical issues related to integration of artificial intelligence and database technologies in order to develop new classes of intelligent information systems. Such combination of artificial intelligence and database technologies is a fast growing subfield of modern computer science, important due to the constant development of networked information systems. New global multimedia systems used by heterogeneous populations call for these developments. The editors hope that the book can be useful for graduate and PhD students of computer science, as well as for mature academics, researchers and practitioners interested in effective application of artificial intelligence and database systems to modern information environments. It is the hope of the editors that readers of this volume can find many inspiring ideas and influential practical examples and use them in their future work.
Research in multi-agent systems offers a promising technology for problems with networks, online trading and negotiations but also social structures and communication. This is a book on agent and multi-agent technolog...
ISBN:
(数字)9783642135262
ISBN:
(纸本)9783642135255
Research in multi-agent systems offers a promising technology for problems with networks, online trading and negotiations but also social structures and communication. This is a book on agent and multi-agent technology for internet and enterprise systems. The book is a pioneer in the combination of the fields and is based on the concept of developing a platform to share ideas and presents research in technology in the field and application to real problems. The chapters range over both applications, illustrating the possible uses of agents in an enterprise domain, and design and analytic methods, needed to provide the solid foundation required for practical systems.
This book presents new algorithms for reinforcement learning, a form of machine learning in which an autonomous agent seeks a control policy for a sequential decision task. Since current methods typically rely on manu...
ISBN:
(数字)9783642139321
ISBN:
(纸本)9783642139314
This book presents new algorithms for reinforcement learning, a form of machine learning in which an autonomous agent seeks a control policy for a sequential decision task. Since current methods typically rely on manually designed solution representations, agents that automatically adapt their own representations have the potential to dramatically improve performance. This book introduces two novel approaches for automatically discovering high-performing representations. The first approach synthesizes temporal difference methods, the traditional approach to reinforcement learning, with evolutionary methods, which can learn representations for a broad class of optimization problems. This synthesis is accomplished by customizing evolutionary methods to the on-line nature of reinforcement learning and using them to evolve representations for value function approximators. The second approach automatically learns representations based on piecewise-constant approximations of value functions. It begins with coarse representations and gradually refines them during learning, analyzing the current policy and value function to deduce the best refinements. This book also introduces a novel method for devising input representations. This method addresses the feature selection problem by extending an algorithm that evolves the topology and weights of neural networks such that it evolves their inputs too. In addition to introducing these new methods, this book presents extensive empirical results in multiple domains demonstrating that these techniques can substantially improve performance over methods with manual representations.
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