BSc(Hons), PhD(Otago)

Senior Lecturer

Email grant.dick@otago.ac.nz

## Background and interests

Associate Professor Grant Dick is a member of the 100-level teaching group and has a background in Information Systems development.

Outside of teaching, his research interests include: Computational Intelligence methods, in particular evolutionary computation; Adaptive business intelligence; Multimodal and multi-objective problem solving; Theoretical population genetics; Evolving systems, particularly the role of population structure in speciation.

Grant is the recipient of a teaching award.

## Research

Grant's overall research goal is to discover intelligent methods to solve difficult real-world problems. Broadly speaking, he is interested in computational intelligence methods and their application to scheduling, optimisation, data mining and multi-objective problem solving.

His primary research interest is in computational intelligence, which attempts to mimic problem solving techniques found in natural systems to solve difficult real-world problems. Computational intelligence methods are often able to reveal solutions to problems where “traditional” methods have previously failed. They are often useful in environments where desirable outcomes are constantly changing, or when complete descriptions of the desired solution are difficult to obtain.

### Background

His PhD thesis explored the use of computational intelligence for multimodal problem solving. The techniques developed in his thesis are applicable to problems that possess potentially many equally-viable solutions. Examples of my work have appeared in internationally-respected journals, such as *IEEE Transactions of Evolutionary Computation, Theoretical Population Biology and Soft Computing*.

### Potential collaborations

- Scheduling and dispatch problems, particularly in dynamic or constrained environments
- Applying computational intelligence techniques to discover anomalous behaviours in customers, patients, or workers
- Optimisation of any problems with multiple conflicting goals (e.g. Cost vs. Time)
- Prediction and forecasting

## Papers

- COMP101 Foundations of Information Systems

## Supervision

### Currently supervising:

- Paul Williams
- Caitlin Owen

### Currently co-supervising:

- Harry Peyhani
- Aladdin Shamoug
- Adriaan Lotter

## Publications

Owen, C. A., Dick, G., & Whigham, P. A. (2020). Characterizing genetic programming
error through extended bias and variance decomposition. *IEEE Transactions on Evolutionary
Computation*, *24*(6), 1164-1176. doi:
10.1109/tevc.2020.2990626

Dick, G., Owen, C. A., & Whigham, P. A. (2020). Feature standardisation and coefficient
optimisation for effective symbolic regression. *Proceedings of the Genetic &
Evolutionary Computation Conference (GECCO).* (pp. 306-314). New York, NY: ACM.
doi: 10.1145/3377930.3390237

Whigham, P. A., Chugh, M., & Dick, G. (2018). Measuring language complexity using
word embeddings. In T. Mitrovic, B. Xue & X. Li (Eds.), *Advances in artifical
intelligence: Lecture notes in artificial intelligence (Vol. 11320).* (pp. 843-854).
Cham, Switzerland: Springer. doi:
10.1007/978-3-030-03991-2_76

Chugh, M., Whigham, P. A., & Dick, G. (2018). Stability of word embeddings using Word2Vec.
In T. Mitrovic, B. Xue & X. Li (Eds.), *Advances in artificial intelligence: Lecture
notes in artificial intelligence (Vol. 11320).* (pp. 812-818). Cham, Switzerland:
Springer. doi: 10.1007/978-3-030-03991-2_73

Owen, C. A., Dick, G., & Whigham, P. A. (2018). Feature standardisation in symbolic
regression. In T. Mitrovic, B. Xue & X. Li (Eds.), *Advances in artifical intelligence:
Lecture notes in artificial intelligence (Vol. 11320).* (pp. 565-576). Cham, Switzerland:
Springer. doi: 10.1007/978-3-030-03991-2_52

Dick, G., & Whigham, P. A. (2008). A weighted local sharing technique for multimodal
optimisation. In X. Li & et al (Eds.), *Simulated evolution and learning: Lecture
notes in computer science (Vol. 5361)*. (pp. 452-461). Berlin, Germany: Springer.

Chapter in Book - Research

Owen, C. A., Dick, G., & Whigham, P. A. (2020). Characterizing genetic programming
error through extended bias and variance decomposition. *IEEE Transactions on Evolutionary
Computation*, *24*(6), 1164-1176. doi:
10.1109/tevc.2020.2990626

Journal - Research Article

Whigham, P. A., Dick, G., & Maclaurin, J. (2017). Just because it works: A response
to comments on "On the mapping of genotype to phenotype in evolutionary algorithms".
*Genetic Programming & Evolvable Machines*, *18*(3), 399-405. doi:
10.1007/s10710-017-9289-9

Journal - Research Article

Whigham, P. A., Dick, G., & Maclaurin, J. (2017). On the mapping of genotype to phenotype
in evolutionary algorithms. *Genetic Programming & Evolvable Machines*, *18*(3),
353-361. doi: 10.1007/s10710-017-9288-x

Journal - Research Article

Whigham, P. A., Dick, G., & Parry, M. (2016). Network rewiring dynamics with convergence
towards a star network. *Proceedings of the Royal Society A*, *472*(2194),
20160236. doi: 10.1098/rspa.2016.0236

Journal - Research Article

Dick, G., & Whigham, P. A. (2011). Weighted local sharing and local clearing for multimodal
optimisation. *Soft Computing*, *15*, 1707-1721. doi:
10.1007/s00500-010-0612-0

Journal - Research Article

Whigham, P. A., & Dick, G. (2010). Implicitly controlling bloat in genetic programming.
*IEEE Transactions on Evolutionary Computation*, *14*(2), 173-190.
doi: 10.1109/tevc.2009.2027314

Journal - Research Article

Dick, G., & Whigham, P. (2008). Spatially-structured sharing technique for multimodal
problems. *Journal of Computer Science & Technology*, *23*(1), 64-76.

Journal - Research Article

Whigham, P. A., & Dick, G. (2008). Evolutionary dynamics for the spatial Moran process.
*Genetic Programming & Evolvable Machines*, *9*(2), 157-170. doi:
10.1007/s10710-007-9046-6

Journal - Research Article

Whigham, P. A., Dick, G. C., & Spencer, H. G. (2008). Genetic drift on networks: Ploidy
and the time to fixation. *Theoretical Population Biology*, *74*(4),
283-290. doi: 10.1016/j.tpb.2008.08.004

Journal - Research Article

Whigham, P. A., Dick, G., & Recknagel, F. (2006). Exploring seasonal patterns using
process modelling and evolutionary computation. *Ecological Modelling*, *195*,
146-152.

Journal - Research Article

Dick, G., Owen, C. A., & Whigham, P. A. (2020). Feature standardisation and coefficient
optimisation for effective symbolic regression. *Proceedings of the Genetic &
Evolutionary Computation Conference (GECCO).* (pp. 306-314). New York, NY: ACM.
doi: 10.1145/3377930.3390237

Conference Contribution - Published proceedings: Full paper

Chugh, M., Whigham, P. A., & Dick, G. (2018). Stability of word embeddings using Word2Vec.
In T. Mitrovic, B. Xue & X. Li (Eds.), *Advances in artificial intelligence: Lecture
notes in artificial intelligence (Vol. 11320).* (pp. 812-818). Cham, Switzerland:
Springer. doi: 10.1007/978-3-030-03991-2_73

Conference Contribution - Published proceedings: Full paper

Dick, G., Owen, C. A., & Whigham, P. A. (2018). Evolving bagging ensembles using a
spatially-structured niching method. *Proceedings of the Genetic and Evolutionary
Computation Conference.* (pp. 418-425). New York, NY: ACM. doi:
10.1145/3205455.3205642

Conference Contribution - Published proceedings: Full paper

Owen, C. A., Dick, G., & Whigham, P. A. (2018). Feature standardisation in symbolic
regression. In T. Mitrovic, B. Xue & X. Li (Eds.), *Advances in artifical intelligence:
Lecture notes in artificial intelligence (Vol. 11320).* (pp. 565-576). Cham, Switzerland:
Springer. doi: 10.1007/978-3-030-03991-2_52

Conference Contribution - Published proceedings: Full paper

Shamoug, A., Cranefield, S., & Dick, G. (2018). Information retrieval for humanitarian
crises via a semantically classified word embedding. In K. Stock & D. Bunker (Eds.),
*Proceedings of the Information Systems for Crisis Response and Management Asia
Pacific 2018 Conference: Innovating for Resilience.* (pp. 132-144). Wellington,
New Zealand: Massey University. [Full Paper]

Conference Contribution - Published proceedings: Full paper

Whigham, P. A., Chugh, M., & Dick, G. (2018). Measuring language complexity using
word embeddings. In T. Mitrovic, B. Xue & X. Li (Eds.), *Advances in artifical
intelligence: Lecture notes in artificial intelligence (Vol. 11320).* (pp. 843-854).
Cham, Switzerland: Springer. doi:
10.1007/978-3-030-03991-2_76

Conference Contribution - Published proceedings: Full paper

Dick, G. (2017). Sensitivity-like analysis for feature selection in genetic programming.
*Proceedings of the Genetic and Evolutionary Computation Conference (GECCO).*
(pp. 401-408). New York, NY: ACM. doi:
10.1145/3071178.3071338

Conference Contribution - Published proceedings: Full paper

Dick, G. (2015). Improving geometric semantic genetic programming with safe tree initialisation.
In P. Machado, M. I. Heywood, J. McDermott, M. Castelli, P. García-Sánchez, P. Burelli,
… K. Sim (Eds.), *Genetic programming: Lecture notes in computer science (Vol.
9025).* (pp. 28-40). Springer. doi:
10.1007/978-3-319-16501-1_3

Conference Contribution - Published proceedings: Full paper

Dick, G., Rimoni, A. P., & Whigham, P. A. (2015). A re-examination of the use of genetic
programming on the oral bioavailability problem. In S. Silva (Ed.), *Proceedings
of the 2015 on Genetic and Evolutionary Computation Conference (GECCO).* (pp.
1015-1022). New York: ACM. doi:
10.1145/2739480.2754771

Conference Contribution - Published proceedings: Full paper

Whigham, P. A., Dick, G., Maclaurin, J., & Owen, C. A. (2015). Examining the "best
of both worlds" of grammatical evolution. *Proceedings of the Genetic and Evolutionary
Computation (GECCO) Conference.* (pp. 1111-1118). New York: ACM. doi:
10.1145/2739480.2754784

Conference Contribution - Published proceedings: Full paper

Dick, G. (2014). Bloat and generalisation in symbolic regression. In G. Dick, W.
N. Browne, P. Whigham, M. Zhang, L. T. Bui, H. Ishibuchi, … K. Tang (Eds.), *Simulated
evolution and learning: Lecture notes in computer science (Vol. 8886).* (pp. 491-502).
Cham, Switerzland: Springer. doi:
10.1007/978-3-319-13563-2

Conference Contribution - Published proceedings: Full paper

Dick, G., & Yao, X. (2014). Model representation and cooperative coevolution for finite-state
machine evolution. *Proceedings of the Congress on Evolutionary Computation (CEC).*
(pp. 2700-2707). IEEE. doi:
10.1109/cec.2014.6900622

Conference Contribution - Published proceedings: Full paper

Dick, G. (2013). A true finite-state baseline for Tartarus. In C. Blum (Ed.), *Proceedings
of the Fifteenth Annual Conference on Genetic and Evolutionary Computation (GECCO).*
(pp. 183-190). New York: ACM. doi:
10.1145/2463372.2463400

Conference Contribution - Published proceedings: Full paper

Dick, G. (2013). An effective parse tree representation for Tartarus. In C. Blum
(Ed.), *Proceedings of the Fifteenth Annual Conference on Genetic and Evolutionary
Computation (GECCO).* (pp. 909-916). New York: ACM. doi:
10.1145/2463372.2463497

Conference Contribution - Published proceedings: Full paper

Dick, G., & Whigham, P. A. (2013). Controlling bloat through parsimonious elitist
replacement and spatial structure. In K. Krawiec, A. Moraglio, T. Hu, A. Ş. Etaner-Uyar
& B. Hu (Eds.), *Genetic programming: Lecture notes in computer science (Vol. 7831).*
(pp. 13-24). Berlin, Germany: Springer. doi:
10.1007/978-3-642-37207-0_2

Conference Contribution - Published proceedings: Full paper

Whigham, P. A., Dick, G., Wright, A., & Spencer, H. G. (2013). Structured populations
and the maintenance of sex. In L. Vanneschi, W. S. Bush & M. Giacobini (Eds.), *Evolutionary
computation, machine learning and data mining in bioinformatics: Lecture notes in
computer science (Vol. 7833).* (pp. 56-67). Berlin, Germany: Springer. doi:
10.1007/978-3-642-37189-9_6

Conference Contribution - Published proceedings: Full paper

Dick, G. (2012). Niche allocation in spatially-structured evolutionary algorithms
with gradients. *Proceedings of the Congress on Evolutionary Computation (CEC).*
doi: 10.1109/CEC.2012.6256542

Conference Contribution - Published proceedings: Full paper

Dick, G. (2010). Automatic identification of the niche radius using spatially-structured
clearing methods. *Proceedings of the IEEE Congress on Evolutionary Computation
(CEC).* (pp. 1264-1271). IEEE. doi:
10.1109/CEC.2010.5586085

Conference Contribution - Published proceedings: Full paper

Dick, G. (2010). The utility of scale factor adaptation in differential evolution.
*Proceedings of the IEEE Congress on Evolutionary Computation (CEC).* (pp.
4355-4362). IEEE. doi: 10.1109/CEC.2010.5586480

Conference Contribution - Published proceedings: Full paper

Whigham, P. A., & Dick, G. (2008). Exploring the use of ancestry as a unified network
model of finite population evolution. *Proceedings of the IEEE Congress on Evolutionary
Computation.* (pp. 3735-3741). Los Alamitos, CA: IEEE Computer Society. [Full
Paper]

Conference Contribution - Published proceedings: Full paper

Dick, G. (2007). The emergence and distribution of species in a gradient-based spatially-structured
evolutionary algorithm. In P. A. Whigham (Ed.), *Proceedings of the 19th Annual
Colloquium of the Spatial Information Research Centre.* (pp. 99-110). Dunedin,
New Zealand: SIRC, University of Otago. [Full Paper]

Conference Contribution - Published proceedings: Full paper

Dick, G. (2006). Evolutionary multiobjective optimisation through spatially-structured
non-dominated sorting: A preliminary study. In P. A. Whigham (Ed.), *Proceedings
of the 18th Annual Colloquium of the Spatial Information Research Centre.* (pp.
87-96). Dunedin, New Zealand: SIRC, University of Otago. [Full Paper]

Conference Contribution - Published proceedings: Full paper

Dick, G., & Whigham, P. A. (2006). Multimodal optimisation with structured populations
and local environments. In T.-D. Wang, X. Li, S.-H. Chen, X. Wang, H. Abbass, H.
Iba, … X. Yao (Eds.), *Proceedings of the 6th International Conference on Simulated
Evolution and Learning.* (pp. 505-512). Berlin, Germany: Springer. [Full Paper]

Conference Contribution - Published proceedings: Full paper

Dick, G., & Whigham, P. A. (2006). Spatially-structured evolutionary algorithms and
sharing: Do they mix? In T.-D. Wang, X. Li, S.-H. Chen, X. Wang, H. Abbass, H. Iba,
… X. Yao (Eds.), *Proceedings of the 6th International Conference on Simulated
Evolution and Learning.* (pp. 457-464). Berlin, Germany: Springer. [Full Paper]

Conference Contribution - Published proceedings: Full paper

Whigham, P. A., & Dick, G. (2006). Evolutionary dynamics on graphs: The Moran Process.
In T.-D. Wang, X. Li, S.-H. Chen, X. Wang, H. Abbass, H. Iba, … X. Yao (Eds.), *Proceedings
of the 6th International Conference on Simulated Evolution and Learning (LNCS 4247).*
(pp. 1-8). Berlin, Germany: Springer. [Full Paper]

Conference Contribution - Published proceedings: Full paper

Whigham, P. A., & Dick, G. (2006). GP and bloat: Absorbing boundaries and spatial
structures. In R. I. McKay, N. X. Hoai & P. T. Long (Eds.), *Proceedings of the
Third Asian-Pacific Workshop on Genetic Programming.* (pp. 1-12). Hanoi, Vietnam:
Military Technical Academy. [Full Paper]

Conference Contribution - Published proceedings: Full paper

Whigham, P., & Dick, G. (2006). How does space alter the formulation of evolutionary
models? In P. A. Whigham (Ed.), *Proceedings of the 18th Annual Colloquium of
the Spatial Information Research Centre.* (pp. 79-84). Dunedin, New Zealand: SIRC,
University of Otago. [Full Paper]

Conference Contribution - Published proceedings: Full paper

Dick, G. (2005). A comparison of localised and global niching methods. In P. A. Wigham
(Ed.), *Proceedings of the 17th Annual Colloquium of the Spatial Information Research
Centre.* (pp. 91-101). [Full Paper]

Conference Contribution - Published proceedings: Full paper

Dick, G., & Whigham, P. (2005). The behaviour of genetic drift in a spatially-structured
evolutionary algorithm. *Proceedings of the IEEE Congress on Evolutionary Computation.*
*2*, (pp. 1855-1860). Piscataway, NJ, USA: IEEE Press. [Full Paper]

Conference Contribution - Published proceedings: Full paper

Dick, G., & Whigham, P. A. (2005). Discovering population structures with extreme
fixation rates via evolutionary search. In P. A. Wigham (Ed.), *Proceedings of
the 17th Annual Colloquium of the Spatial Information Research Centre.* (pp.
175-179). [Full Paper]

Conference Contribution - Published proceedings: Full paper

Whigham, P. A., & Dick, G. (2005). Fixation of neural alleles in spatially structures
populations via genetic drift: Describing the spatial structure of faster-than-panmictic
configurations. In P. A. Wigham (Ed.), *Proceedings of the 17th Annual Colloquium
of the Spatial Information Research Centre.* (pp. 81-90). [Full Paper]

Conference Contribution - Published proceedings: Full paper

Dick, G. (2004). A general framework for describing spatially-structured populations
in evolutionary computation. In P. A. Wigham & B. R. McLennan (Eds.), *Proceedings
of the 16th Annual Colloquium of the Spatial Information Research Centre.* (pp.
117-126). [Full Paper]

Conference Contribution - Published proceedings: Full paper

Dick, G. (2004). An empirical investigation into correlation functions in a spatially-dispersed
evolutionary algorithm. In P. A. Wigham & B. R. McLennan (Eds.), *Proceedings
of the 16th Annual Colloquium of the Spatial Information Research Centre.* (pp.
23-33). [Full Paper]

Conference Contribution - Published proceedings: Full paper

Jang, D. K., Whigham, P. A., & Dick, G. (2004). On evolving fixed pattern strategies
for Iterated Prisoner's Dilemma. *Proceedings of the 27th Australasian Computer
Science Conference.* (pp. 241-248). [Full Paper]

Conference Contribution - Published proceedings: Full paper

Dick, G. (2003). An explicit spatial model for niching in genetic algorithms. In
P. A. Wigham & A. Moore (Eds.), *Proceedings of the 15th Annual Colloquium of
the Spatial Information Research Centre.* (pp. 151-157). [Full Paper]

Conference Contribution - Published proceedings: Full paper

Dick, G. (2003). The spatially-dispersed genetic algorithm: An explicit spatial population
structure for gas. In A. Abraham, M. Koppen & K. Franke (Eds.), *Proceedings of
the Congress on Evolutionary Computation.* (pp. 2455-2461). [Full Paper]

Conference Contribution - Published proceedings: Full paper

Middlemiss, M., & Dick, G. (2003). Feature selection of intrusion detection data using
a Hybrid Genetic Algorithm/KNN Approach. In A. Abraham, M. Koppen & K. Franke (Eds.),
*Design and Application of Hybrid Intelligent Systems.* (pp. 519-527). [Full
Paper]

Conference Contribution - Published proceedings: Full paper

Middlemiss, M., & Dick, G. (2003). Weighted feature extraction using a genetic algorithm
for intrusion detection. In A. Abraham, M. Koppen & K. Franke (Eds.), *Proceedings
of the Congress on Evolutionary Computation.* (pp. 1669-1675). [Full Paper]

Conference Contribution - Published proceedings: Full paper

Whigham, P. A., & Dick, G. (2003). A Voromoi-based distributed genetic algorithm.
In P. A. Wigham & A. Moore (Eds.), *Proceedings of the 15th Annual Colloquium
of the Spatial Information Research Centre.* (pp. 133-138). [Full Paper]

Conference Contribution - Published proceedings: Full paper