Explore our research

Date


School

Download Available

52 results

Use of machine learning techniques to model wind damage to forests

Journal Article
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...

Quantifying the effects of increasing user choice in MAP-Elites applied to a Workforce Scheduling and Routing Problem.

Conference Proceeding
Urquhart, N., Hart, E., & Hutcheson, W. (2019)
Quantifying the effects of increasing user choice in MAP-Elites applied to a Workforce Scheduling and Routing Problem. In EvoApplications 2019: Applications of Evolutionary Computation, 49-63. https://doi.org/10.1007/978-3-030-16692-2_4
Quality-diversity algorithms such as MAP-Elites provide a means of supporting the users when finding and choosing solutions to a problem by returning a set of solutions which ...

Controlling a simulated Khepera with an XCS classifier system with memory.

Conference Proceeding
Webb, A., Hart, E., Ross, P. & Lawson, A. (2003)
Controlling a simulated Khepera with an XCS classifier system with memory. ISBN 9783540200574
Autonomous agents commonly suffer from perceptual aliasing in which differing situations are perceived as identical by the robots sensors, yet require different courses of act...

The Cost of Communication: Environmental Pressure and Survivability in mEDEA

Conference Proceeding
Steyven, A., Hart, E., & Paechter, B. (2015)
The Cost of Communication: Environmental Pressure and Survivability in mEDEA. In Proceedings of the Companion Publication of the 2015 on Genetic and Evolutionary Computation Conference - GECCO Companion '15, 1239-1240. doi:10.1145/2739482.2768489
We augment the mEDEA algorithm to explicitly account for the costs of communication between robots. Experimental results show that adding a costs for communication exerts envi...

Using an evolutionary algorithm to discover low CO2 tours within a Travelling Salesman Problem

Conference Proceeding
Urquhart, N. B., Scott, C., & Hart, E. (2010)
Using an evolutionary algorithm to discover low CO2 tours within a Travelling Salesman Problem. In C. Chio, A. Brabazon, G. A. Di Caro, M. Ebner, M. Farooq, A. Fink, …N. Urquhart (Eds.), Applications of evolutionary computation : EvoApplications 2010: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoMUSART, and EvoTRANSLOG, Istanbul, Turkey, April 7-9, 2010, Proceedings, Part II, (421-430). https://doi.org/10.1007/978-3-642-12242-2_43
This paper examines the issues surrounding the effects of using vehicle emissions as the fitness criteria when solving routing problems using evolutionary techniques. The case...

Understanding Environmental Influence in an Open-Ended Evolutionary Algorithm

Conference Proceeding
Steyven, A., Hart, E., & Paechter, B. (2016)
Understanding Environmental Influence in an Open-Ended Evolutionary Algorithm. In Parallel Problem Solving from Nature – PPSN XIV; Lecture Notes in Computer Science, 921-931. https://doi.org/10.1007/978-3-319-45823-6_86
It is well known that in open-ended evolution, the nature of the environment plays in key role in directing evolution. However, in Evolutionary Robotics, it is often unclear e...

An investigation of environmental influence on the benefits of adaptation mechanisms in evolutionary swarm robotics

Conference Proceeding
Steyven, A., Hart, E., & Paechter, B. (2017)
An investigation of environmental influence on the benefits of adaptation mechanisms in evolutionary swarm robotics. In GECCO '17 Proceedings of the Genetic and Evolutionary, (155-162). https://doi.org/10.1145/3071178.3071232
A robotic swarm that is required to operate for long periods in a potentially unknown environment can use both evolution and individual learning methods in order to adapt. How...

A hybrid method for feature construction and selection to improve wind-damage prediction in the forestry sector

Conference Proceeding
Hart, E., Sim, K., Gardiner, B., & Kamimura, K. (2017)
A hybrid method for feature construction and selection to improve wind-damage prediction in the forestry sector. In GECCO '17 Proceedings of the Genetic and Evolutionary Computation Conference, (1121-1128). https://doi.org/10.1145/3071178.3071217
Catastrophic damage to forests resulting from major storms has resulted in serious timber and financial losses within the sector across Europe in the recent past. Developing r...

Impact of selection methods on the diversity of many-objective Pareto set approximations

Journal Article
Martí, L., Segredo, E., Sánchez-Pi, N., & Hart, E. (2017)
Impact of selection methods on the diversity of many-objective Pareto set approximations. Procedia Computer Science, 112, (844-853). ISSN 1877-0509
Selection methods are a key component of all multi-objective and, consequently, many-objective optimisation evolutionary algorithms. They must perform two main tasks simultane...

Multi-Modal employee routing with time windows in an urban environment.

Conference Proceeding
Urquhart, N. B., Hart, E., & Judson, A. (2015)
Multi-Modal employee routing with time windows in an urban environment. In Proceedings of the 2015 Genetic and Evolutionary Algorithms Conference, (1503-1504). https://doi.org/10.1145/2739482.2764649
An urban environment provides a number of challenges and opportunities for organisations faced with the task of scheduling a mobile workforce. Given a mixed set of public and ...
7 results

Ensembles for Optimisation

2015 - 2016
Optimisation – finding cost-effective or high-performing solutions - is a key economic driver for business today. However, academic literature on search-based optimisation techniques reflects an escal...
Funder: Leverhulme Trust | Value: £34,465

Autonomous Robot Evolution: Cradle to Grave

2018 - 2022
Robotics is changing the landscape of innovation. But traditional design approaches are not suited to novel or unknown habitats and contexts, for instance: robot colonies for ore mining, exploring or ...
Funder: Engineering and Physical Sciences Research Council | Value: £366,412

Towards Guided Self-Organisation in Artificial Complex Systems: A Swarm Robotics Case Study

2020 - 2022
Swarm robotics refers to the design and coordination of large numbers of simple physical robots. Uses include environmental applications such as pollution monitoring in the oceans using aquatic robots...
Funder: Royal Society | Value: £11,500

Hyperheuristics for infrastructure system optimisation

2020 - 2020
Continuum Industries novel software tech allows engineers to automate their work and evaluate millions of possible combinations of design parameters. Primary application lies in linear infrastructure ...
Funder: Data Lab | Value: £19,599

FOCAS

2013 - 2016
FOCAS is a coordination action in the area of collective adaptive systems. It provides increased visibility to the research carried out by projects funded by the FOCAS FET Proactive Initiative and oth...
Funder: European Commission | Value: £639,999

Life Long Learning Hyper Heuristic Optimisation

2012 - 2015
This project aims to improve the current state of the art in developing optimisation tools which are relevant and acceptable to industry. This will be achieved by addressing industrial current concer...
Funder: Engineering and Physical Sciences Research Council | Value: £238,068

KTP: Intelligent Agents

2019 - 2022
Improving customer experience through intelligent workflow
Funder: Innovate UK | Value: £268,152
13 results

Prof. Emma Hart invited to join Scottish Government Steering Group to develop an Artificial Intelligence (AI) strategy for Scotland.

16 September 2019
Prof. Emma Hart has been invited by Minister Kate Forbes to join a Scottish Government Steering Group to develop an Artificial Intelligence (AI) strategy for Scotland.

Researchers from Nature-Inspired Intelligent Systems group win Best Paper Award@GECCO 2019

16 July 2019
PhD student Mohamad Alissa with supervisors Dr Kevin Sim and Prof. Emma Hart won the Best Paper award in the ECOM track at GECCO 2019 in Prague for their paper: Algorithm Selection Using Deep Learnin...

Prof . Emma Hart gives interview "An Insider's Guide to Evolutionary Computation"

17 December 2018
Laura van Beers from ContactEngine, a London based company delivering software that enables its customers to proactively engage customers in AI-driven conversations to fulfil their business objective...

Prof. Emma Hart invited to talk at Scotland IS Software Engineering Leader's Forum to discuss SICSA's work on AI

20 November 2018
Prof. Emma Hart gave an invited talk at the monthly meet-up of the Scotland IS Software Engineering forum on behalf of the SICSA AI theme to describe the work taking place across Scottish Universities...

Prof. Emma Hart interviewed in new video released by Sentient AI to provide unique insights to business leaders on the growing applicability of evolutionary computation

13 August 2018
Sentient Technologies, a world leader in artificial intelligence (AI) products based on evolutionary computation, today announced a new video collection that provides unique insights to the burgeonin...

Prof. Emma Hart and Dr Kevin Sim win Bronze Award in International Humies competition for work on predicting wind damage in Forestry

18 July 2018
The Annual Humies prize is awarded at the International Conference on Genetic and Evolutionary Computation for human-competitive results that have been produced by any form of genetic and evolutionar...

Evolutionary Robotics Research Nominated for Best Paper Award

14 July 2018
Prof. Emma Hart, Dr Andreas Steyven and Prof. Ben Paechter have been nominated for a prestigious best paper award at the GECCO 18, Kyoto, Japan for new work in evolving a diverse team of swarm robot...

Prof. Emma Hart invited as a keynote speaker at IJCCI in Funchal, Madeira, November 2017

1 November 2017
The International Joint Conference on Computational Intelligence brings together researchers, engineers and practitioners interested in the field of Computational Intelligence both from theoretical an...

CAVES researchers have 3 papers accepted at GECCO 2017

14 July 2017
Members of the CAVES research group have 3 papers accepted at the world's leading conference on Evolutionary Computing. GECCO 2017 will be held in Berlin from 15-19th July 2017. Accepted papers are: ...

Prof. Emma Hart interview with MIT Press on her new Editor-in-Chief role

17 February 2017
The New Year welcomed Emma Hart to the helm of Evolutionary Computation. She took over the role of Editor-in-Chief from Hans-Georg Beyer (who had assumed the role himself in 2010). Professor Hart ans...