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Mor g a n C l aypool Pu b l i s h e r s
&
w w w . m o r g a n c l a y p o o l . c o m
Series Editors:
Ronald J. Brachman, Yahoo! Research, William Cohen, Carnegie Mellon University,
and Thomas G. Dietterich, Oregon State University
MOR G A N & CLAY P OOL
C
M
&
Mor g a n C l ay p o ol Publishers
&
SYNTHESIS LECTURES ON ARTIF ICIAL
INTELLIGENCE AND MACHINE LEARNING
SYNTHESIS LECTURES ON ARTIF ICIAL
INTELLIGENCE AND MACHINE LEARNING
About SYNTHESIs
This volume is a printed version of a work that appears in the Synthesis
Digital Library of Engineering and Computer Science. Synthesis Lectures
provide concise, original presentations of important research and development
topics, published quickly, in digital and print formats. For more information
visit www.morganclaypool.com
Ronald J. Brachman, William Cohen, and Thomas G. Dietterich, Series Editors
ISBN: 978-1-60845-516-4
9 781608 455164
90000
Series ISSN: 1939-4608
HUMAN COMPUTATION
LAW • VON AHN
Human Computation
Edith Law and Luis von Ahn, Carnegie Mellon University
Human computation is a new and evolving research area that centers around harnessing human
intelligence to solve computational problems that are beyond the scope of existing Artificial Intelligence
(AI) algorithms. With the growth of the Web, human computation systems can now leverage the
abilities of an unprecedented number of people via theWeb to perform complex computation. There
are various genres of human computation applications that exist today. Games with a purpose (e.g.,
the ESP Game) specifically target online gamers who generate useful data (e.g., image tags) while
playing an enjoyable game. Crowdsourcing marketplaces (e.g., Amazon MechanicalTurk) are human
computation systems that coordinate workers to perform tasks in exchange for monetary rewards.
In identity verification tasks, users perform computation in order to gain access to some online
content; an example is reCAPTCHA, which leverages millions of users who solve CAPTCHAs
every day to correct words in books that optical character recognition (OCR) programs fail to
recognize with certainty.
This book is aimed at achieving four goals: (1) defining human computation as a research area;
(2) providing a comprehensive review of existing work; (3) drawing connections to a wide variety
of disciplines, including AI, Machine Learning, HCI, Mechanism/Market Design and Psychology,
and capturing their unique perspectives on the core research questions in human computation; and
(4) suggesting promising research directions for the future.
Human Computation
Edith Law
Luis von Ahn
Mor g a n C l aypool Pu b l i s h e r s
&
w w w . m o r g a n c l a y p o o l . c o m
Series Editors:
Ronald J. Brachman, Yahoo! Research, William Cohen, Carnegie Mellon University,
and Thomas G. Dietterich, Oregon State University
MOR G A N & CLAY P OOL
C
M
&
Mor g a n C l ay p o ol Publishers
&
SYNTHESIS LECTURES ON ARTIF ICIAL
INTELLIGENCE AND MACHINE LEARNING
SYNTHESIS LECTURES ON ARTIF ICIAL
INTELLIGENCE AND MACHINE LEARNING
About SYNTHESIs
This volume is a printed version of a work that appears in the Synthesis
Digital Library of Engineering and Computer Science. Synthesis Lectures
provide concise, original presentations of important research and development
topics, published quickly, in digital and print formats. For more information
visit www.morganclaypool.com
Ronald J. Brachman, William Cohen, and Thomas G. Dietterich, Series Editors
ISBN: 978-1-60845-516-4
9 781608 455164
90000
Series ISSN: 1939-4608
HUMAN COMPUTATION
LAW • VON AHN
Human Computation
Edith Law and Luis von Ahn, Carnegie Mellon University
Human computation is a new and evolving research area that centers around harnessing human
intelligence to solve computational problems that are beyond the scope of existing Artificial Intelligence
(AI) algorithms. With the growth of the Web, human computation systems can now leverage the
abilities of an unprecedented number of people via theWeb to perform complex computation. There
are various genres of human computation applications that exist today. Games with a purpose (e.g.,
the ESP Game) specifically target online gamers who generate useful data (e.g., image tags) while
playing an enjoyable game. Crowdsourcing marketplaces (e.g., Amazon MechanicalTurk) are human
computation systems that coordinate workers to perform tasks in exchange for monetary rewards.
In identity verification tasks, users perform computation in order to gain access to some online
content; an example is reCAPTCHA, which leverages millions of users who solve CAPTCHAs
every day to correct words in books that optical character recognition (OCR) programs fail to
recognize with certainty.
This book is aimed at achieving four goals: (1) defining human computation as a research area;
(2) providing a comprehensive review of existing work; (3) drawing connections to a wide variety
of disciplines, including AI, Machine Learning, HCI, Mechanism/Market Design and Psychology,
and capturing their unique perspectives on the core research questions in human computation; and
(4) suggesting promising research directions for the future.
Human Computation
Edith Law
Luis von Ahn
Mor g a n C l aypool Pu b l i s h e r s
&
w w w . m o r g a n c l a y p o o l . c o m
Series Editors:
Ronald J. Brachman, Yahoo! Research, William Cohen, Carnegie Mellon University,
and Thomas G. Dietterich, Oregon State University
MOR G A N & CLAY P OOL
C
M
&
Mor g a n C l ay p o ol Publishers
&
SYNTHESIS LECTURES ON ARTIF ICIAL
INTELLIGENCE AND MACHINE LEARNING
SYNTHESIS LECTURES ON ARTIF ICIAL
INTELLIGENCE AND MACHINE LEARNING
About SYNTHESIs
This volume is a printed version of a work that appears in the Synthesis
Digital Library of Engineering and Computer Science. Synthesis Lectures
provide concise, original presentations of important research and development
topics, published quickly, in digital and print formats. For more information
visit www.morganclaypool.com
Ronald J. Brachman, William Cohen, and Thomas G. Dietterich, Series Editors
ISBN: 978-1-60845-516-4
9 781608 455164
90000
Series ISSN: 1939-4608
HUMAN COMPUTATION
LAW • VON AHN
Human Computation
Edith Law and Luis von Ahn, Carnegie Mellon University
Human computation is a new and evolving research area that centers around harnessing human
intelligence to solve computational problems that are beyond the scope of existing Artificial Intelligence
(AI) algorithms. With the growth of the Web, human computation systems can now leverage the
abilities of an unprecedented number of people via theWeb to perform complex computation. There
are various genres of human computation applications that exist today. Games with a purpose (e.g.,
the ESP Game) specifically target online gamers who generate useful data (e.g., image tags) while
playing an enjoyable game. Crowdsourcing marketplaces (e.g., Amazon MechanicalTurk) are human
computation systems that coordinate workers to perform tasks in exchange for monetary rewards.
In identity verification tasks, users perform computation in order to gain access to some online
content; an example is reCAPTCHA, which leverages millions of users who solve CAPTCHAs
every day to correct words in books that optical character recognition (OCR) programs fail to
recognize with certainty.
This book is aimed at achieving four goals: (1) defining human computation as a research area;
(2) providing a comprehensive review of existing work; (3) drawing connections to a wide variety
of disciplines, including AI, Machine Learning, HCI, Mechanism/Market Design and Psychology,
and capturing their unique perspectives on the core research questions in human computation; and
(4) suggesting promising research directions for the future.
Human Computation
Edith Law
Luis von Ahn
Human Computation
Synthesis Lectures on Artificial
Intelligence and Machine
Learning
Editors
Ronald J. Brachman, Yahoo Research
William W. Cohen, Carnegie Mellon University
Thomas Dietterich, Oregon State University
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
iii
Introduction to Semi-Supervised Learning
Xiaojin Zhu 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
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