عنوان
پدید آورنده
موضوع
رده
Q325.6 .K85 2012
Q325
.
6
.
K85
2012
کتابخانه
محل استقرار
INTERNATIONAL STANDARD BOOK NUMBER
(Number (ISBN
047091999X
(Number (ISBN
1118266501 (electronic bk.)
(Number (ISBN
111827153X (electronic bk.)
(Number (ISBN
9780470919996
(Number (ISBN
9781118266502 (electronic bk.)
(Number (ISBN
9781118271537 (electronic bk.)
NATIONAL BIBLIOGRAPHY NUMBER
Number
dltt
TITLE AND STATEMENT OF RESPONSIBILITY
Title Proper
Reinforcement and systemic machine learning for decision making /
General Material Designation
[Book]
First Statement of Responsibility
Parag Kulkarni.
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
1 online resource (422 pages).
SERIES
Series Title
IEEE Press Series on Systems Science and Engineering ;
Volume Designation
v.1
GENERAL NOTES
Text of Note
7.3 Multiperspective Decision Making And Multiperspective Learning
CONTENTS NOTE
Text of Note
Chapter 1: Introduction to Reinforcement and Systemic Machine Learning; 1.1 Introduction; 1.2 Supervised, Unsupervised, and Semisupervised Machine Learning; 1.3 Traditional Learning Methods and History of Machine Learning; 1.4 What is Machine Learning?; 1.5 Machine-Learning Problem; 1.6 Learning Paradigms; 1.7 Machine-Learning Techniques and Paradigms; 1.8 What is Reinforcement Learning?; 1.9 Reinforcement Function and Environment Function; 1.10 Need of Reinforcement Learning
Text of Note
1.11 Reinforcement Learning and Machine Intelligence1.12 What is Systemic Learning?; 1.13 What Is Systemic Machine Learning?; 1.14 Challenges in Systemic Machine Learning; 1.15 Reinforcement Machine Learning and Systemic Machine Learning; 1.16 Case Study Problem Detection in a Vehicle; 1.17 Summary; Reference; Chapter 2: Fundamentals of Whole-System, Systemic, and Multiperspective Machine Learning; 2.1 Introduction; 2.2 What is Systemic Machine Learning?; 2.3 Generalized Systemic Machine-Learning Framework; 2.4 Multiperspective Decision Making and Multiperspective Learning
Text of Note
2.5 Dynamic and Interactive Decision Making2.6 The Systemic Learning Framework; 2.7 System Analysis; 2.8 Case Study: Need of Systemic Learning in the Hospitality Industry; 2.9 Summary; References; Chapter 3: Reinforcement Learning; 3.1 Introduction; 3.2 Learning Agents; 3.3 Returns and Reward Calculations; 3.4 Reinforcement Learning and Adaptive Control; 3.5 Dynamic Systems; 3.6 Reinforcement Learning and Control; 3.7 Markov Property and Markov Decision Process; 3.8 Value Functions; 3.9 Learning An Optimal Policy (Model-Based and Model-Free Methods); 3.10 Dynamic Programming
Text of Note
3.11 Adaptive Dynamic Programming3.12 Example: Reinforcement Learning for Boxing Trainer; 3.13 Summary; Reference; Chapter 4: Systemic Machine Learning and Model; 4.1 Introduction; 4.2 A Framework for Systemic Learning; 4.3 Capturing THE Systemic View; 4.4 Mathematical Representation of System Interactions; 4.5 Impact Function; 4.6 Decision-Impact Analysis; 4.7 Summary; Chapter 5: Inference and Information Integration; 5.1 Introduction; 5.2 Inference Mechanisms and Need; 5.3 Integration of Context and Inference; 5.4 Statistical Inference and Induction; 5.5 Pure Likelihood Approach
Text of Note
5.6 Bayesian Paradigm and Inference5.7 Time-Based Inference; 5.8 Inference to Build a System View; 5.9 Summary; References; Chapter 6: Adaptive Learning; 6.1 Introduction; 6.2 Adaptive Learning and Adaptive Systems; 6.3 What is Adaptive Machine Learning?; 6.4 Adaptation and Learning Method Selection Based on Scenario; 6.5 Systemic Learning and Adaptive Learning; 6.6 Competitive Learning and Adaptive Learning; 6.7 Examples; 6.8 Summary; References; Chapter 7: Multiperspective and Whole-System Learning; 7.1 Introduction; 7.2 Multiperspective Context Building
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8
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SUMMARY OR ABSTRACT
Text of Note
Reinforcement and Systemic Machine Learning for Decision MakingThere are always difficulties in making machines that learn from experience. Complete information is not always available--or it becomes available in bits and pieces over a period of time. With respect to systemic learning, there is a need to understand the impact of decisions and actions on a system over that period of time. This book takes a holistic approach to addressing that need and presents a new paradigm--creating new learning applications and, ultimately, more intelligent machines.The first book of its kind in this new and g
OTHER EDITION IN ANOTHER MEDIUM
Title
Reinforcement and Systemic Machine Learning for Decision Making
International Standard Book Number
9780470919996
TOPICAL NAME USED AS SUBJECT
Decision making.
Machine learning.
Reinforcement learning.
Computer science.
Decision Making.
Machine learning.
Reinforcement learning.
Science.
TECHNOLOGY & ENGINEERING / Electronics / General.
(SUBJECT CATEGORY (Provisional
COM-- 004000
COM-- 005030
DEWEY DECIMAL CLASSIFICATION
Number
006
.
31
LIBRARY OF CONGRESS CLASSIFICATION
Class number
Q325
.
6
Book number
.
K85
2012
PERSONAL NAME - PRIMARY RESPONSIBILITY
Kulkarni, Parag.
CORPORATE BODY NAME - ALTERNATIVE RESPONSIBILITY
Ohio Library and Information Network.
Wiley Online Library (Online service)
ORIGINATING SOURCE
Date of Transaction
20130111115256.0
Cataloguing Rules (Descriptive Conventions))
rda
ELECTRONIC LOCATION AND ACCESS
Electronic name
مطالعه متن کتاب [Book]
Y
