reinforcement learning state of the art adaptation learning and optimization

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Reinforcement Learning

Author : Marco Wiering
ISBN : 9783642276453
Genre : Computers
File Size : 38. 91 MB
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Reinforcement learning encompasses both a science of adaptive behavior of rational beings in uncertain environments and a computational methodology for finding optimal behaviors for challenging problems in control, optimization and adaptive behavior of intelligent agents. As a field, reinforcement learning has progressed tremendously in the past decade. The main goal of this book is to present an up-to-date series of survey articles on the main contemporary sub-fields of reinforcement learning. This includes surveys on partially observable environments, hierarchical task decompositions, relational knowledge representation and predictive state representations. Furthermore, topics such as transfer, evolutionary methods and continuous spaces in reinforcement learning are surveyed. In addition, several chapters review reinforcement learning methods in robotics, in games, and in computational neuroscience. In total seventeen different subfields are presented by mostly young experts in those areas, and together they truly represent a state-of-the-art of current reinforcement learning research. Marco Wiering works at the artificial intelligence department of the University of Groningen in the Netherlands. He has published extensively on various reinforcement learning topics. Martijn van Otterlo works in the cognitive artificial intelligence group at the Radboud University Nijmegen in The Netherlands. He has mainly focused on expressive knowledge representation in reinforcement learning settings.

Handbuch Der K Nstlichen Intelligenz

Author : Günther Görz
ISBN : 9783486719796
Genre : Computers
File Size : 35. 84 MB
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Das Handbuch der Künstlichen Intelligenz vereint einführende und weiterführende Beiträge u.a. zu folgenden Themen: - Neuronale Netze - Maschinelles Lernen und Data Mining - Semantic Web - Multiagentensysteme - Bildverstehen - Robotik Die 17 Kapitel von über 30 renommierten Autoren lassen sich unabhängig von einander lesen und machen das Werk zu einem aktuellen Handbuch und flexibel in der Lehre einsetzbaren Referenzwerk.

International Joint Conference Soco 14 Cisis 14 Iceute 14

Author : José Gaviria de la Puerta
ISBN : 9783319079950
Genre : Computers
File Size : 90. 73 MB
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This volume of Advances in Intelligent and Soft Computing contains accepted papers presented at SOCO 2014, CISIS 2014 and ICEUTE 2014, all conferences held in the beautiful and historic city of Bilbao (Spain), in June 2014. Soft computing represents a collection or set of computational techniques in machine learning, computer science and some engineering disciplines, which investigate, simulate, and analyze very complex issues and phenomena. After a through peer-review process, the 9th SOCO 2014 International Program Committee selected 31 papers which are published in these conference proceedings. In this relevant edition a special emphasis was put on the organization of special sessions. One special session was organized related to relevant topics as: Soft Computing Methods in Manufacturing and Management Systems. The aim of the 7th CISIS 2014 conference is to offer a meeting opportunity for academic and industry-related researchers belonging to the various, vast communities of Computational Intelligence, Information Security, and Data Mining. The need for intelligent, flexible behaviour by large, complex systems, especially in mission-critical domains, is intended to be the catalyst and the aggregation stimulus for the overall event. After a through peer-review process, the CISIS 2014 International Program Committee selected 23 papers and the 5th ICEUTE 2014 International Program Committee selected 2 papers which are published in these conference proceedings as well.

Natural And Artificial Computation In Engineering And Medical Applications

Author : José Manuel Ferrández Vicente
ISBN : 9783642386220
Genre : Computers
File Size : 45. 53 MB
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The two volume-set, LNCS 7930 and LNCS 7931, constitutes the refereed proceedings of the 5th International Work-Conference on the Interplay between Natural and Artificial Computation, IWINAC 2013, held in Mallorca, Spain, in June 2013. The 92 revised full papers presented in LNCS 7930 and LNCS 7931 were carefully reviewed and selected from numerous submissions. The first part, LNCS 7930, entitled "Natural and Artificial Models in Computation and Biology”, includes all the contributions mainly related to the methodological, conceptual, formal, and experimental developments in the fields of neurophysiology and cognitive science. The second part, LNCS 7931, entitled “Natural and Artificial Computation in Engineering and Medical Applications”, contains the papers related to bioinspired programming strategies and all the contributions related to the computational solutions to engineering problems in different application domains, specially Health applications, including the CYTED “Artificial and Natural Computation for Health” (CANS) research network papers. In addition, this two volume-set reflects six interesting areas: cognitive robotics; natural computing; wetware computation; quality of life technologies; biomedical and industrial perception applications; and Web intelligence and neuroscience.

Scalable Uncertainty Management

Author : Steven Schockaert
ISBN : 9783319458564
Genre : Computers
File Size : 60. 80 MB
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This book constitutes the refereed proceedings of the 10th International Conference on Scalable Uncertainty Management, SUM 2016, held in Nice, France, in September 2016. The 18 regular papers and 5 short papers were carefully reviewed and selected from 35 submissions. Papers are solicited in all areas of managing and reasoning with substantial and complex kinds of uncertain, incomplete or inconsistent information. These include (but are not restricted to) applications in decision support systems, risk analysis, machine learning, belief networks, logics of uncertainty, belief revision and update, argumentation, negotiation technologies, semantic web applications, search engines, ontology systems, information fusion, information retrieval, natural language processing, information extraction, image recognition, vision systems, data and text mining, and the consideration of issues such as provenance, trust, heterogeneity, and complexity of data and knowledge.

Proceedings Of The Third International Scientific Conference Intelligent Information Technologies For Industry Iiti 18

Author : Ajith Abraham
ISBN : 9783030018214
Genre :
File Size : 39. 83 MB
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Statistical Reinforcement Learning

Author : Masashi Sugiyama
ISBN : 9781439856901
Genre : Business & Economics
File Size : 23. 16 MB
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Reinforcement learning is a mathematical framework for developing computer agents that can learn an optimal behavior by relating generic reward signals with its past actions. With numerous successful applications in business intelligence, plant control, and gaming, the RL framework is ideal for decision making in unknown environments with large amounts of data. Supplying an up-to-date and accessible introduction to the field, Statistical Reinforcement Learning: Modern Machine Learning Approaches presents fundamental concepts and practical algorithms of statistical reinforcement learning from the modern machine learning viewpoint. It covers various types of RL approaches, including model-based and model-free approaches, policy iteration, and policy search methods. Covers the range of reinforcement learning algorithms from a modern perspective Lays out the associated optimization problems for each reinforcement learning scenario covered Provides thought-provoking statistical treatment of reinforcement learning algorithms The book covers approaches recently introduced in the data mining and machine learning fields to provide a systematic bridge between RL and data mining/machine learning researchers. It presents state-of-the-art results, including dimensionality reduction in RL and risk-sensitive RL. Numerous illustrative examples are included to help readers understand the intuition and usefulness of reinforcement learning techniques. This book is an ideal resource for graduate-level students in computer science and applied statistics programs, as well as researchers and engineers in related fields.

Selbst Ndig Lernende Neuronale Steuerungen

Author : Martin Riedmiller
ISBN : 318362608X
Genre :
File Size : 57. 6 MB
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Anticipatory Learning Classifier Systems

Author : Martin V. Butz
ISBN : 9781461508915
Genre : Computers
File Size : 22. 5 MB
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Anticipatory Learning Classifier Systems describes the state of the art of anticipatory learning classifier systems-adaptive rule learning systems that autonomously build anticipatory environmental models. An anticipatory model specifies all possible action-effects in an environment with respect to given situations. It can be used to simulate anticipatory adaptive behavior. Anticipatory Learning Classifier Systems highlights how anticipations influence cognitive systems and illustrates the use of anticipations for (1) faster reactivity, (2) adaptive behavior beyond reinforcement learning, (3) attentional mechanisms, (4) simulation of other agents and (5) the implementation of a motivational module. The book focuses on a particular evolutionary model learning mechanism, a combination of a directed specializing mechanism and a genetic generalizing mechanism. Experiments show that anticipatory adaptive behavior can be simulated by exploiting the evolving anticipatory model for even faster model learning, planning applications, and adaptive behavior beyond reinforcement learning. Anticipatory Learning Classifier Systems gives a detailed algorithmic description as well as a program documentation of a C++ implementation of the system.

Das Geheimnis Des Menschlichen Denkens

Author : Ray Kurzweil
ISBN : 9783944203164
Genre : Science
File Size : 84. 6 MB
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Der Wettlauf um das Gehirn hat begonnen. Sowohl die EU als auch die USA haben gewaltige Forschungsprojekte ins Leben gerufen um das Geheimnis des menschlichen Denkens zu entschlüsseln. 2023 soll es dann soweit sein: Das menschliche Gehirn kann vollständig simuliert werden. In "Das Geheimnis des menschlichen Denkens" gewährt Googles Chefingenieur Ray Kurzweil einen spannenden Einblick in das Reverse Engineering des Gehirns. Er legt dar, wie mithilfe der Mustererkennungstheorie des Geistes der ungeheuren Komplexität des Gehirns beizukommen ist und wirft einen ebenso präzisen wie überraschenden Blick auf die am Horizont sich bereits abzeichnende Zukunft. Ist das menschliche Gehirn erst einmal simuliert, wird künstliche Intelligenz die Fähigkeiten des Menschen schon bald übertreffen. Ein Ereignis, das Kurzweil aufgrund der bereits in "Menschheit 2.0" entworfenen exponentiellen Wachstumskurve der Informationstechnologien bereits für das Jahr 2029 prognostiziert. Aber was dann? Kurzweil ist zuversichtlich, dass die Vorteile künstlicher Intelligenz mögliche Bedrohungsszenarien überwiegen und sie uns entscheidend dabei hilft, uns weiterzuentwickeln und die Herausforderungen der Zukunft zu meistern.

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