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Research Areas : Optimisation and learning x Dewey Decimal : 0063 Artificial intelligence x Themes : Information Society x

Outputs (55)

Artificial Immune Systems (Dagstuhl Seminar 11172)

Hart, E., Jansen, T. & Timmis, J. (2010). Artificial Immune Systems (Dagstuhl Seminar 11172)
Hart, E., Jansen, T. & Timmis, J. (2010). Artificial Immune Systems (Dagstuhl Seminar 11172)

This report documents the program and the outcomes of the Dagstuhl Seminar 11172 ``Artificial Immune Systems''. The purpose of the seminar was to bring together researchers fr...

2010
Use of machine learning techniques to model wind damage to forests

Hart, E., Sim, K., Kamimura, K., Meredieu, C., Guyon, D., & Gardiner, B. (2019). Use of machine learning techniques to model wind damage to forests. Agricultural and forest meteorology, 265, 16-29. https://doi.org/10.1016/j.agrformet.2018.10.022
Hart, E., Sim, K., Kamimura, K., Meredieu, C., Guyon, D., & Gardiner, B. (2019). Use of machine learning techniques to model wind damage to forests. Agricultural and forest meteorology, 265, 16-29. https://doi.org/10.1016/j.agrformet.2018.10.022

This paper tested the ability of machine learning techniques, namely artificial neural networks and random forests, to predict the individual trees within a forest most at r...

2018
A hyper-heuristic ensemble method for static job-shop scheduling.

Hart, E., & Sim, K. (2016). A hyper-heuristic ensemble method for static job-shop scheduling. Evolutionary Computation, 24(4), 609-635. https://doi.org/10.1162/EVCO_a_00183
Hart, E., & Sim, K. (2016). A hyper-heuristic ensemble method for static job-shop scheduling. Evolutionary Computation, 24(4), 609-635. https://doi.org/10.1162/EVCO_a_00183

We describe a new hyper-heuristic method NELLI-GP for solving job-shop scheduling problems (JSSP) that evolves an ensemble of heuristics. The ensemble adopts a divide-and-conq...

2016
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Research Areas : Optimisation and learning x Dewey Decimal : 0063 Artificial intelligence x Themes : Information Society x

Artificial Immune Systems (Dagstuhl Seminar 11172)

Hart, E., Jansen, T. & Timmis, J. (2010). Artificial Immune Systems (Dagstuhl Seminar 11172)
Hart, E., Jansen, T. & Timmis, J. (2010). Artificial Immune Systems (Dagstuhl Seminar 11172)

This report documents the program and the outcomes of the Dagstuhl Seminar 11172 ``Artificial Immune Systems''. The purpose of the seminar was to bring together researchers fr...

2010
Use of machine learning techniques to model wind damage to forests

Hart, E., Sim, K., Kamimura, K., Meredieu, C., Guyon, D., & Gardiner, B. (2019). Use of machine learning techniques to model wind damage to forests. Agricultural and forest meteorology, 265, 16-29. https://doi.org/10.1016/j.agrformet.2018.10.022
Hart, E., Sim, K., Kamimura, K., Meredieu, C., Guyon, D., & Gardiner, B. (2019). Use of machine learning techniques to model wind damage to forests. Agricultural and forest meteorology, 265, 16-29. https://doi.org/10.1016/j.agrformet.2018.10.022

This paper tested the ability of machine learning techniques, namely artificial neural networks and random forests, to predict the individual trees within a forest most at r...

2018
A hyper-heuristic ensemble method for static job-shop scheduling.

Hart, E., & Sim, K. (2016). A hyper-heuristic ensemble method for static job-shop scheduling. Evolutionary Computation, 24(4), 609-635. https://doi.org/10.1162/EVCO_a_00183
Hart, E., & Sim, K. (2016). A hyper-heuristic ensemble method for static job-shop scheduling. Evolutionary Computation, 24(4), 609-635. https://doi.org/10.1162/EVCO_a_00183

We describe a new hyper-heuristic method NELLI-GP for solving job-shop scheduling problems (JSSP) that evolves an ensemble of heuristics. The ensemble adopts a divide-and-conq...

2016
A Lifelong Learning Hyper-heuristic Method for Bin Packing.

Hart, E., Sim, K., & Paechter, B. (2015). A Lifelong Learning Hyper-heuristic Method for Bin Packing. Evolutionary Computation, 23(1), 37-67. https://doi.org/10.1162/EVCO_a_00121
Hart, E., Sim, K., & Paechter, B. (2015). A Lifelong Learning Hyper-heuristic Method for Bin Packing. Evolutionary Computation, 23(1), 37-67. https://doi.org/10.1162/EVCO_a_00121

We describe a novel Hyper-heuristic system which continuously learns over time to solve a combinatorial optimisation problem. The system continuously generates new heuristics ...

2015
A fuzzy logic controller applied to a diversity-based multi-objective evolutionary algorithm for single-objective optimisation

Segredo, E., Seguro, C., Coromoto, L., & Hart, E. (2014). A fuzzy logic controller applied to a diversity-based multi-objective evolutionary algorithm for single-objective optimisation. Soft Computing, 19(10), 2927-2945. https://doi.org/10.1007/s00500-014-1454-y
Segredo, E., Seguro, C., Coromoto, L., & Hart, E. (2014). A fuzzy logic controller applied to a diversity-based multi-objective evolutionary algorithm for single-objective optimisation. Soft Computing, 19(10), 2927-2945. https://doi.org/10.1007/s00500-014-1454-y

In recent years, Multi-Objective Evolutionary Algorithms (MOEAS) that consider diversity as an objective have been used to tackle single-objective optimisation prob- lems. The...

2014
Techniques for Auditing the ICT Carbon Footprint of an Organisation

Mouchet, C., Urquhart, N., & Kemmer, R. (2014). Techniques for Auditing the ICT Carbon Footprint of an Organisation. International Journal of Green Computing, 5(1), 44-61. https://doi.org/10.4018/ijgc.2014010104
Mouchet, C., Urquhart, N., & Kemmer, R. (2014). Techniques for Auditing the ICT Carbon Footprint of an Organisation. International Journal of Green Computing, 5(1), 44-61. https://doi.org/10.4018/ijgc.2014010104

This article has presents an extensive survey of the state of the art in Green IT/S. The findings of the survey suggest that there is scope for a reliable carbon footprint aud...

2014
Automated scheduling and planning; from theory to practice.

(2013). S. Etaner-Uyar, E. Ozcan, & N. B. Urquhart (Eds.), Automated scheduling and planning; from theory to practice. Springer Verlag. https://doi.org/10.1007/978-3-642-39304-4
(2013). S. Etaner-Uyar, E. Ozcan, & N. B. Urquhart (Eds.), Automated scheduling and planning; from theory to practice. Springer Verlag. https://doi.org/10.1007/978-3-642-39304-4

2013
Artificial Immune Systems: 9th International Conference, ICARIS 2010, Edinburgh, UK, July 26-29, 2010, Proceedings

(2010). E. Hart, C. McEwan, J. Timmis, & A. Hone (Eds.), Artificial Immune Systems: 9th International Conference, ICARIS 2010, Edinburgh, UK, July 26-29, 2010, Proceedings. BMC. https://doi.org/10.1007/978-3-642-14547-6
(2010). E. Hart, C. McEwan, J. Timmis, & A. Hone (Eds.), Artificial Immune Systems: 9th International Conference, ICARIS 2010, Edinburgh, UK, July 26-29, 2010, Proceedings. BMC. https://doi.org/10.1007/978-3-642-14547-6

Artificial immune systems (AIS) is a diverse and maturing area of research that bridges the disciplines of immunology and computation. The original research impetus in AIS had...

2010
On artificial immune systems and swarm intelligence

Timmis, J., Andrews, P., & Hart, E. (2010). On artificial immune systems and swarm intelligence. Swarm Intelligence, 4(4), 247-273. doi:10.1007/s11721-010-0045-5
Timmis, J., Andrews, P., & Hart, E. (2010). On artificial immune systems and swarm intelligence. Swarm Intelligence, 4(4), 247-273. doi:10.1007/s11721-010-0045-5

This position paper explores the nature and role of two bio-inspired paradigms, namely Artificial Immune Systems (AIS) and Swarm Intelligence (SI). We argue that there are man...

2010
Representation in the (Artificial) Immune System.

McEwan, C., & Hart, E. (2009). Representation in the (Artificial) Immune System. Journal of Mathematical Modelling and Algorithms, 8, 125-149. https://doi.org/10.1007/s10852-009-9104-6
McEwan, C., & Hart, E. (2009). Representation in the (Artificial) Immune System. Journal of Mathematical Modelling and Algorithms, 8, 125-149. https://doi.org/10.1007/s10852-009-9104-6

Much of contemporary research in Artificial Immune Systems (AIS) has partitioned into either algorithmic machine learning and optimisation, or, modelling biologically plausibl...

2009
Structure versus function: a topological perspective on immune networks.

Hart, E., Bersini, H., & Santos, F. (2009). Structure versus function: a topological perspective on immune networks. Natural Computing, https://doi.org/10.1007/s11047-009-9138-8
Hart, E., Bersini, H., & Santos, F. (2009). Structure versus function: a topological perspective on immune networks. Natural Computing, https://doi.org/10.1007/s11047-009-9138-8

Many recent advances have been made in understanding the functional implications of the global topological properties of biological networks through the application of complex...

2009
Application areas of AIS: The past, the present and the future

Hart, E., & Timmis, J. (2008). Application areas of AIS: The past, the present and the future. Applied Soft Computing, 8(1), 191-201. doi:10.1016/j.asoc.2006.12.004
Hart, E., & Timmis, J. (2008). Application areas of AIS: The past, the present and the future. Applied Soft Computing, 8(1), 191-201. doi:10.1016/j.asoc.2006.12.004

After a decade of research into the area of artificial immune systems, it is worthwhile to take a step back and reflect on the contributions that the paradigm has brought to t...

2008
The ARE Robot Fabricator: How to (Re)produce Robots that Can Evolve in the Real World

Hale, M. F., Buchanan, E., Winfield, A. F., Timmis, J., Hart, E., Eiben, A. E., …Tyrrell, A. M. (2019). The ARE Robot Fabricator: How to (Re)produce Robots that Can Evolve in the Real World. In ALIFE 2019: The 2019 Conference on Artificial Life, 95-102. https://doi.org/10.1162/isal_a_00147
Hale, M. F., Buchanan, E., Winfield, A. F., Timmis, J., Hart, E., Eiben, A. E., …Tyrrell, A. M. (2019). The ARE Robot Fabricator: How to (Re)produce Robots that Can Evolve in the Real World. In ALIFE 2019: The 2019 Conference on Artificial Life, 95-102. https://doi.org/10.1162/isal_a_00147

The long term vision of the Autonomous Robot Evolution (ARE) project is to create an ecosystem of both virtual and physical robots with evolving brains and bodies. One of the ...

2019
Athos - A Model Driven Approach to Describe and Solve Optimisation Problems

Hoffman, B., Chalmers, K., Urquhart, N., & Guckert, M. (2019). Athos - A Model Driven Approach to Describe and Solve Optimisation Problems. https://doi.org/10.1145/3300111.3300114
Hoffman, B., Chalmers, K., Urquhart, N., & Guckert, M. (2019). Athos - A Model Driven Approach to Describe and Solve Optimisation Problems. https://doi.org/10.1145/3300111.3300114

Implementing solutions for optimisation problems with general purpose high-level programming languages is a time consuming task that can only be carried out by professional so...

2019
A novel similarity-based mutant vector generation strategy for differential evolution

Segredo, E., Lalla-Ruiz, E., & Hart, E. (2017). A novel similarity-based mutant vector generation strategy for differential evolution. In H. Aguirre (Ed.), Proceedings of the Genetic and Evolutionary Computation Conference 2018
Segredo, E., Lalla-Ruiz, E., & Hart, E. (2017). A novel similarity-based mutant vector generation strategy for differential evolution. In H. Aguirre (Ed.), Proceedings of the Genetic and Evolutionary Computation Conference 2018

The mutant vector generation strategy is an essential component of Differential Evolution (DE), introduced to promote diversity, resulting in exploration of novel areas of the...

2018

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Research Areas : Optimisation and learning x Dewey Decimal : 0063 Artificial intelligence x Themes : Information Society x

Edinburgh Napier University

Staff directory

Outputs (55)

Artificial Immune Systems (Dagstuhl Seminar 11172)

Use of machine learning techniques to model wind damage to forests

A hyper-heuristic ensemble method for static job-shop scheduling.

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Dewey Decimal

Artificial Immune Systems (Dagstuhl Seminar 11172)

Use of machine learning techniques to model wind damage to forests

A hyper-heuristic ensemble method for static job-shop scheduling.

A Lifelong Learning Hyper-heuristic Method for Bin Packing.

A fuzzy logic controller applied to a diversity-based multi-objective evolutionary algorithm for single-objective optimisation

Techniques for Auditing the ICT Carbon Footprint of an Organisation

Automated scheduling and planning; from theory to practice.

Artificial Immune Systems: 9th International Conference, ICARIS 2010, Edinburgh, UK, July 26-29, 2010, Proceedings

On artificial immune systems and swarm intelligence

Representation in the (Artificial) Immune System.

Structure versus function: a topological perspective on immune networks.

Application areas of AIS: The past, the present and the future

The ARE Robot Fabricator: How to (Re)produce Robots that Can Evolve in the Real World

Athos - A Model Driven Approach to Describe and Solve Optimisation Problems

A novel similarity-based mutant vector generation strategy for differential evolution

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Date

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