Shoping cart:
Empty
Cheap Software
Search by Letter:
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All programs New Mac

Multi-Objective Decision Making

1$
Buy!Download Size: 1.55 MB

× Multi-Objective Decision Making Close
Multi-Objective Decision Making
Morgan & Claypool | English | 2017 | ISBN-10: 1627059601 | 129 pages | PDF | 1.55 mb
by Diederik M Roijers (Author), Shimon Whiteson (Author), Ronald Brachman (Editor)

Many real-world decision problems have multiple objectives. For example, when choosing a medical treatment plan, we want to maximize the efficacy of the treatment, but also minimize the side effects. These objectives typically conflict, e.g., we can often increase the efficacy of the treatment, but at the cost of more severe side effects. In this book, we outline how to deal with multiple objectives in decision-theoretic planning and reinforcement learning algorithms. To illustrate this, we employ the popular problem classes of multi-objective Markov decision processes (MOMDPs) and multi-objective coordination graphs (MO-CoGs).

First, we discuss different use cases for multi-objective decision making, and why they often necessitate explicitly multi-objective algorithms. We advocate a utility-based approach to multi-objective decision making, i.e., that what constitutes an optimal solution to a multi-objective decision problem should be derived from the available information about user utility. We show how different assumptions about user utility and what types of policies are allowed lead to different solution concepts, which we outline in a taxonomy of multi-objective decision problems.

Second, we show how to create new methods for multi-objective decision making using existing single-objective methods as a basis. Focusing on planning, we describe two ways to creating multi-objective algorithms: in the inner loop approach, the inner workings of a single-objective method are adapted to work with multi-objective solution concepts; in the outer loop approach, a wrapper is created around a single-objective method that solves the multi-objective problem as a series of single-objective problems. After discussing the creation of such methods for the planning setting, we discuss how these approaches apply to the learning setting.

Next, we discuss three promising application domains for multi-objective decision making algorithms: energy, health, and infrastructure and transportation. Finally, we conclude by outlining important open problems and promising future directions.


Multi-Objective Decision Making

1$
Buy!Download Size: 1.55 MB


Customers who bought this program also bought:


Wiley Statistical Pattern Recognition 3rd Edition 2011 PDF eBook $10 BUY!
Mosek Optimization Tools 7.0.0.85 x64 $10 BUY!
Evolutionary Multi-Criterion Optimization PDF eBook $10 BUY!
An Introduction to Optimization, 4th Edition PDF eBook $1 BUY!
Handbook of Optimization From Classical to Modern Approach PDF eBook $1 BUY!
PTC MathCAD 15.0 M045 (1 cd) $50 BUY!
50 Most Powerful Excel Functions and Formulas advanced ways to save your time and make complex analysis quick and easy MS Excel training Book 1 PDF eBook $1 BUY!
Minitab 18.1 $25 BUY!
Statistical Relational Artificial Intelligence Logic, Probability, and Computation $1 BUY!
Pattern Recognition And Big Data $1 BUY!
Lifelong Machine Learning $1 BUY!
Multi-Objective Optimization Problems Concepts and Self-Adaptive Parameters with Mathematical and Engineering Applications $1 BUY!
Machine Learning and Data Mining in Pattern Recognition $1 BUY!


Software Store Deal of the Day

2010 SUPER PACK 4

2010 SUPER PACK 4

Unclude: Adobe Acrobat 9.0 Pro Extended (1 dvd), Adobe Photoshop CS5 Extended 12.0 (1 dvd), Autodesk Autocad LT 2011 (1 dvd), Corel WinDVD Pro 2010 10.0.5.291 Multilingual, CorelDRAW Graphics Suite X5 15.0.0.486, DVD Cloner VII 7.10.992, TechSmith Camtasia Studio 7.0.0

Real PriceSaving Deal of the Day View it »
$2960 94.6%229$BUY!
We recommend
Categories
© 2010-2017. All rights reserved.