Multi-Objective Decision Making. Diederik M. Roijers

Multi-Objective Decision Making - Diederik M. Roijers


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       Multi-Objective Decision Making

       Synthesis Lectures on Artificial Intelligence and Machine Learning

      Editors

       Ronald J. Brachman, Yahoo! Labs

       Peter Stone, University of Texas at Austin

      Multi-Objective Decision Making

      Diederik M. Roijers and Shimon Whiteson

      2017

      Lifelong Machine Learning

      Zhiyuan Chen and Bing Liu

      2016

      Statistical Relational Artificial Intelligence: Logic, Probability, and Computation

      Luc De Raedt, Kristian Kersting, Sriraam Natarajan, and David Poole

      2016

      Representing and Reasoning with Qualitative Preferences: Tools and Applications

      Ganesh Ram Santhanam, Samik Basu, and Vasant Honavar

      2016

      Metric Learning

      Aurélien Bellet, Amaury Habrard, and MarcSebban

      2015

      Graph-Based Semi-Supervised Learning

      Amarnag Subramanya and Partha Pratim Talukdar

      2014

      Robot Learning from Human Teachers

      Sonia Chernova and Andrea L. Thomaz

      2014

      General Game Playing

      Michael Genesereth and Michael Thielscher

      2014

      Judgment Aggregation: A Primer

      Davide Grossi and Gabriella Pigozzi

      2014

      An Introduction to Constraint-Based Temporal Reasoning

      Roman Barták, Robert A. Morris, and K. Brent Venable

      2014

      Reasoning with Probabilistic and Deterministic Graphical Models: Exact Algorithms

      Rina Dechter

      2013

      Introduction to Intelligent Systems in Traffic and Transportation

      Ana L.C. Bazzan and Franziska Klügl

      2013

      A Concise Introduction to Models and Methods for Automated Planning

      Hector Geffner and Blai Bonet

      2013

      Essential Principles for Autonomous Robotics

      Henry Hexmoor

      2013

      Case-Based Reasoning: A Concise Introduction

      Beatriz López

      2013

      Answer Set Solving in Practice

      Martin Gebser, Roland Kaminski, Benjamin Kaufmann, and Torsten Schaub

      2012

      Planning with Markov Decision Processes: An AI Perspective

      Mausam and Andrey Kolobov

      2012

      Active Learning

      Burr Settles

      2012

      Computational Aspects of Cooperative Game Theory

      Georgios Chalkiadakis, Edith Elkind, and Michael Wooldridge

      2011

      Representations and Techniques for 3D Object Recognition and Scene Interpretation

      Derek Hoiem and Silvio Savarese

      2011

      A Short Introduction to Preferences: Between Artificial Intelligence and Social Choice

      Francesca Rossi, Kristen Brent Venable, and Toby Walsh

      2011

      Human Computation

      Edith Law and Luis von Ahn

      2011

      Trading Agents

      Michael P. Wellman

      2011

      Visual Object Recognition

      Kristen Grauman and Bastian Leibe

      2011

      Learning with Support Vector Machines

      Colin Campbell and Yiming Ying

      2011

      Algorithms for Reinforcement Learning

      Csaba Szepesvári

      2010

      Data Integration: The Relational Logic Approach

      Michael Genesereth

      2010

      Markov Logic: An Interface Layer for Artificial Intelligence

      Pedro Domingos and Daniel Lowd

      2009

      Introduction to Semi-Supervised Learning

      XiaojinZhu and Andrew B. Goldberg

      2009

      Action Programming Languages

      Michael Thielscher

      2008

      Representation Discovery using Harmonic Analysis

      Sridhar Mahadevan

      2008

      Essentials of Game Theory: A Concise Multidisciplinary Introduction

      Kevin Leyton-Brown and Yoav Shoham

      2008

      A Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence

      Nikos Vlassis

      2007

      Intelligent Autonomous Robotics: A Robot Soccer Case Study

      Peter Stone

      2007

      Copyright © 2017 by Morgan & Claypool

      All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means—electronic, mechanical, photocopy, recording, or any other except for brief quotations in printed reviews, without the prior permission of the publisher.

      Multi-Objective Decision Making

      Diederik M. Roijers and Shimon Whiteson

       www.morganclaypool.com

      ISBN: 9781627059602 paperback

      ISBN: 9781627056991 ebook

      DOI 10.2200/S00765ED1V01Y201704AIM034

      A Publication in the Morgan & Claypool Publishers series

       SYNTHESIS LECTURES ON ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING

      Lecture #34

      Series Editors: Ronald J. Brachman, Yahoo! Labs

      Peter Stone, University of Texas at Austin

      Series ISSN

      Print 1939-4608 Electronic 1939-4616

       Multi-Objective Decision Making


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