NDLI: A Utile Function Optimizer

Content Provider	IEEE Xplore Digital Library
Author	Monson, C.K. Seppi, K.D. Carroll, J.L.
Copyright Year	2007
Description	Author affiliation: Google Inc., Pittsburgh (Monson, C.K.)
Abstract	We recast the problem of unconstrained continuous evolutionary optimization as inference in a fixed graphical model. This approach allows us to address several pervasive issues in optimization, including the traditionally difficult problem of selecting an algorithm that is most appropriate for a given task. This is accomplished by placing a prior distribution over the expected class of functions, then employing inference and intuitively defined utilities and costs to transform the evolutionary optimization problem into one of active sampling. This allows us to pose an approach to optimization that is optimal for each expressly stated function class. The resulting solution methodology can optimally navigate exploration-exploitation tradeoffs using well-motivated decision theory, while providing the process with a natural stopping criterion. Finally, the model naturally accommodates the expression of dynamic and noisy functions, setting it apart from most existing algorithms that address these issues as an afterthought. We demonstrate the characteristics and advantages of this algorithm formally and with examples.
Starting Page	1067
Ending Page	1074
File Size	210446
Page Count	8
File Format	PDF
ISBN	9781424413393
DOI	10.1109/CEC.2007.4424588
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-09-25
Publisher Place	Singapore
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Graphical models Inference algorithms Sampling methods Bayesian methods Evolutionary computation Computer science Cost function Navigation Decision theory Uncertainty
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Evolutionary Aggregation and Refinement of Bayesian Networks

A utile function optimizer (2007)

Bayesian evolutionary algorithms for continuous function optimization

Learning Bayesian network structure from environment and sensor planning for mobile robot localization

Dependency based reasoning in a dempster-shafer theoretic framework

Sensor planning for mobile robot localization using Bayesian network representation and inference

A Novel Hybrid Evolutionary Algorithm for Learning Bayesian Networks from Incomplete Data

A guided evolutionary computation technique as function optimizer

Devising a cost effective baseball scheduling by evolutionary algorithms

A Utile Function Optimizer

Similar Documents

Evolutionary Aggregation and Refinement of Bayesian Networks

A utile function optimizer (2007)

Bayesian evolutionary algorithms for continuous function optimization

Learning Bayesian network structure from environment and sensor planning for mobile robot localization

Dependency based reasoning in a dempster-shafer theoretic framework

Sensor planning for mobile robot localization using Bayesian network representation and inference

A Novel Hybrid Evolutionary Algorithm for Learning Bayesian Networks from Incomplete Data

A guided evolutionary computation technique as function optimizer

Devising a cost effective baseball scheduling by evolutionary algorithms

A Utile Function Optimizer