Optimisation and fitness modelling of bio-control in mushroom farming using a Markov network eda

Alexander Brownlee; Wu Yanghui; John A.W. McCall; Paul M. Godley; David Cairns; Julie Cowie

doi:10.1145/1389095.1389180

Optimisation and fitness modelling of bio-control in mushroom farming using a Markov network eda

Alexander Brownlee^*, Wu Yanghui, John A.W. McCall, Paul M. Godley, David Cairns, Julie Cowie

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

7 Citations (Scopus)

Abstract

We explore the application of an Estimation of Distribution Algorithm which uses a Markov Network to the problem of bio-control in mushroom farming. This falls into the category of “bang-bang control” problems and was previously used as an application for genetic algorithms with modified crossover operators. The EDA yields a small improvement in the solutions that are evolved. Moreover, the probabilistic models constructed closely match identifiable features in the underlying dynamics of the problem. We conclude that this is a useful by-product of the probabilistic modelling which can be further exploited. probabilistic model learned by DEUM. We will describe how a clear relationship can be drawn between probabilistic model and the underlying shape of the problem.

Original language	English
Title of host publication	GECCO'08
Subtitle of host publication	Proceedings of the 10th Annual Conference on Genetic and Evolutionary Computation 2008
Editors	Maarten Keijizer
Place of Publication	New York
Publisher	Association for Computing Machinery (ACM)
Pages	465-466
Number of pages	2
ISBN (Print)	9781605581316
DOIs	https://doi.org/10.1145/1389095.1389180
Publication status	Published - 30 Nov 2007
Externally published	Yes
Event	10th Annual Genetic and Evolutionary Computation Conference, GECCO 2008 - Atlanta, GA, United States Duration: 12 Jul 2008 → 16 Jul 2008

Conference

Conference	10th Annual Genetic and Evolutionary Computation Conference, GECCO 2008
Country/Territory	United States
City	Atlanta, GA
Period	12/07/08 → 16/07/08

ASJC Scopus subject areas

Computational Theory and Mathematics
Computer Science Applications
Software

Documents and Links

10.1145/1389095.1389180

Cite this

Brownlee, A., Yanghui, W., McCall, J. A. W., Godley, P. M., Cairns, D., & Cowie, J. (2007). Optimisation and fitness modelling of bio-control in mushroom farming using a Markov network eda. In M. Keijizer (Ed.), GECCO'08: Proceedings of the 10th Annual Conference on Genetic and Evolutionary Computation 2008 (pp. 465-466). Association for Computing Machinery (ACM). https://doi.org/10.1145/1389095.1389180

@inproceedings{42d09227cfda457faefc0840ce696271,

title = "Optimisation and fitness modelling of bio-control in mushroom farming using a Markov network eda",

abstract = "We explore the application of an Estimation of Distribution Algorithm which uses a Markov Network to the problem of bio-control in mushroom farming. This falls into the category of “bang-bang control” problems and was previously used as an application for genetic algorithms with modified crossover operators. The EDA yields a small improvement in the solutions that are evolved. Moreover, the probabilistic models constructed closely match identifiable features in the underlying dynamics of the problem. We conclude that this is a useful by-product of the probabilistic modelling which can be further exploited. probabilistic model learned by DEUM. We will describe how a clear relationship can be drawn between probabilistic model and the underlying shape of the problem.",

author = "Alexander Brownlee and Wu Yanghui and McCall, {John A.W.} and Godley, {Paul M.} and David Cairns and Julie Cowie",

year = "2007",

month = nov,

day = "30",

doi = "10.1145/1389095.1389180",

language = "English",

isbn = "9781605581316",

pages = "465--466",

editor = "Maarten Keijizer",

booktitle = "GECCO'08",

publisher = "Association for Computing Machinery (ACM)",

address = "United States",

note = "10th Annual Genetic and Evolutionary Computation Conference, GECCO 2008 ; Conference date: 12-07-2008 Through 16-07-2008",

}

Brownlee, A, Yanghui, W, McCall, JAW, Godley, PM, Cairns, D & Cowie, J 2007, Optimisation and fitness modelling of bio-control in mushroom farming using a Markov network eda. in M Keijizer (ed.), GECCO'08: Proceedings of the 10th Annual Conference on Genetic and Evolutionary Computation 2008. Association for Computing Machinery (ACM), New York, pp. 465-466, 10th Annual Genetic and Evolutionary Computation Conference, GECCO 2008, Atlanta, GA, United States, 12/07/08. https://doi.org/10.1145/1389095.1389180

Optimisation and fitness modelling of bio-control in mushroom farming using a Markov network eda. / Brownlee, Alexander; Yanghui, Wu; McCall, John A.W. et al.
GECCO'08: Proceedings of the 10th Annual Conference on Genetic and Evolutionary Computation 2008. ed. / Maarten Keijizer. New York: Association for Computing Machinery (ACM), 2007. p. 465-466.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Optimisation and fitness modelling of bio-control in mushroom farming using a Markov network eda

AU - Brownlee, Alexander

AU - Yanghui, Wu

AU - McCall, John A.W.

AU - Godley, Paul M.

AU - Cairns, David

AU - Cowie, Julie

PY - 2007/11/30

Y1 - 2007/11/30

N2 - We explore the application of an Estimation of Distribution Algorithm which uses a Markov Network to the problem of bio-control in mushroom farming. This falls into the category of “bang-bang control” problems and was previously used as an application for genetic algorithms with modified crossover operators. The EDA yields a small improvement in the solutions that are evolved. Moreover, the probabilistic models constructed closely match identifiable features in the underlying dynamics of the problem. We conclude that this is a useful by-product of the probabilistic modelling which can be further exploited. probabilistic model learned by DEUM. We will describe how a clear relationship can be drawn between probabilistic model and the underlying shape of the problem.

AB - We explore the application of an Estimation of Distribution Algorithm which uses a Markov Network to the problem of bio-control in mushroom farming. This falls into the category of “bang-bang control” problems and was previously used as an application for genetic algorithms with modified crossover operators. The EDA yields a small improvement in the solutions that are evolved. Moreover, the probabilistic models constructed closely match identifiable features in the underlying dynamics of the problem. We conclude that this is a useful by-product of the probabilistic modelling which can be further exploited. probabilistic model learned by DEUM. We will describe how a clear relationship can be drawn between probabilistic model and the underlying shape of the problem.

U2 - 10.1145/1389095.1389180

DO - 10.1145/1389095.1389180

M3 - Conference contribution

SN - 9781605581316

SP - 465

EP - 466

BT - GECCO'08

A2 - Keijizer, Maarten

PB - Association for Computing Machinery (ACM)

CY - New York

T2 - 10th Annual Genetic and Evolutionary Computation Conference, GECCO 2008

Y2 - 12 July 2008 through 16 July 2008

ER -

Brownlee A, Yanghui W, McCall JAW, Godley PM, Cairns D, Cowie J. Optimisation and fitness modelling of bio-control in mushroom farming using a Markov network eda. In Keijizer M, editor, GECCO'08: Proceedings of the 10th Annual Conference on Genetic and Evolutionary Computation 2008. New York: Association for Computing Machinery (ACM). 2007. p. 465-466 doi: 10.1145/1389095.1389180

Optimisation and fitness modelling of bio-control in mushroom farming using a Markov network eda

Abstract

Conference

ASJC Scopus subject areas

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