Abstract
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 10th annual conference on Genetic and evolutionary computation |
| Editors | Maarten Keijizer |
| Place of Publication | New York |
| Publisher | ACM |
| Pages | 465-466 |
| Number of pages | 2 |
| ISBN (Print) | 9781605581316 |
| DOIs | |
| Publication status | Published - 30 Nov 2007 |
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Keywords
- Optimisation
- EDA
- Optimal Control
- Genetics Mathematical models
- Genetics Computer simulation
- Control theory
Cite this
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Optimisation and fitness modelling of bio-control in mushroom farming using a Markov network eda. / Brownlee, Alexander; Wu, Yanghui; McCall, John; Godley, Paul ; Cairns, David; Cowie, Julie.
Proceedings of the 10th annual conference on Genetic and evolutionary computation. ed. / Maarten Keijizer. New York : 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 - Wu, Yanghui
AU - McCall, John
AU - Godley, Paul
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.
KW - Optimisation
KW - EDA
KW - Optimal Control
KW - Genetics Mathematical models
KW - Genetics Computer simulation
KW - Control theory
U2 - 10.1145/1389095.1389180
DO - 10.1145/1389095.1389180
M3 - Conference contribution
SN - 9781605581316
SP - 465
EP - 466
BT - Proceedings of the 10th annual conference on Genetic and evolutionary computation
A2 - Keijizer, Maarten
PB - ACM
CY - New York
ER -