On the challenges of jointly optimising robot morphology and control using a hierarchical optimisation scheme
Conference Proceeding
Goff, L. K. L., & Hart, E. (2021)
On the challenges of jointly optimising robot morphology and control using a hierarchical optimisation scheme. In GECCO '21: Proceedings of the Genetic and Evolutionary Computation Conference Companion (1498-1502). https://doi.org/10.1145/3449726.3463156
We investigate a hierarchical scheme for the joint optimisation of robot bodies and controllers in a complex morphological space. An evolutionary algorithm optimises body-plan...
Clustering Moving Data with a Modified Immune Algorithm
Conference Proceeding
Hart, E., & Ross, P. (2001)
Clustering Moving Data with a Modified Immune Algorithm. In E. Boers (Ed.), Applications of Evolutionary Computing, 394-403. https://doi.org/10.1007/3-540-45365-2_41
In this paper we present a prototype of a new model for performing clustering in large, non-static databases. Although many machine learning algorithms for data clustering hav...
Evaluation of a genetic representation for outline shapes
Conference Proceeding
Lapok, P., Lawson, A., & Paechter, B. (2017)
Evaluation of a genetic representation for outline shapes. In GECCO '17 Proceedings of the Genetic and Evolutionary Computation Conference Companion, (1419-1422). https://doi.org/10.1145/3067695.3082501
This work in progress focuses on the evaluation of a genetic representation for outline shapes for planar mechanical levers which addresses the first stage of the complex real...
AGADE how individual guidance leads to group behaviour and how this can be simulated
Conference Proceeding
Farrenkopf, T., Guckert, M., Hoffmann, B., & Urquhart, N. B. (2014)
AGADE how individual guidance leads to group behaviour and how this can be simulated. In J. Muller, M. Weyrich, & A. Bazzan (Eds.), Multiagent System Technologies. , (234-250). https://doi.org/10.1007/978-3-319-11584-9_16
In this paper we will demonstrate how BDI agents can be used to model individuals as participants in social structures where they act as potential buyers in a simple mobile ph...
Selection methods and diversity preservation in many-objective evolutionary algorithms
Journal Article
Martí, L., Segredo, E., Sánchez-Pi, N., & Hart, E. (2018)
Selection methods and diversity preservation in many-objective evolutionary algorithms. Data Technologies and Applications, https://doi.org/10.1108/dta-01-2018-0009
Purpose – One of the main components of multi-objective, and therefore, many-objective evolutionary algorithms is the selection mechanism. It is responsible for performing two...
Nature Inspired Optimisation for Delivery Problems: From Theory to the Real World
Book
Urquhart, N. (2022)
Nature Inspired Optimisation for Delivery Problems: From Theory to the Real World. Cham: Springer. https://doi.org/10.1007/978-3-030-98108-2
This book explains classic routing and transportation problems and solutions, before offering insights based on successful real-world solutions. The chapters in Part I introdu...
Hybrid parameter control approach applied to a diversity-based multi-objective Memetic Algorithm for frequency assignment problems
Conference Proceeding
Segredo, E., Paechter, B., Hart, E., & Gonz´alez-Vila, C. I. (2016)
Hybrid parameter control approach applied to a diversity-based multi-objective Memetic Algorithm for frequency assignment problems. In 2016 IEEE Congress on Evolutionary Computation (CEC)https://doi.org/10.1109/CEC.2016.7743969
In order to address the difficult issue of parameter setting within a diversity-based Multi-objective Evolutionary Algorithm (MOEA), we recently proposed a hybrid control sche...
Finding Fair Negotiation Algorithms to Reduce Peak Electricity Consumption in Micro Grids
Conference Proceeding
Powers, S. T., Meanwell, O., & Cai, Z. (2019)
Finding Fair Negotiation Algorithms to Reduce Peak Electricity Consumption in Micro Grids. In PAAMS 2019: Advances in Practical Applications of Survivable Agents and Multi-Agent Systems: The PAAMS Collection, 269-272. https://doi.org/10.1007/978-3-030-24209-1_28
Reducing peak electricity consumption is important to maximise use of renewable energy sources, and reduce the total amount of capacity required on a grid. Most approaches use...
Lifelong Learning Machines: Towards Developing Optimisation Systems That Continually Learn
Book Chapter
Hart, E. (2022)
Lifelong Learning Machines: Towards Developing Optimisation Systems That Continually Learn. In A. E. Smith (Ed.), Women in Computational Intelligence: Key Advances and Perspectives on Emerging Topics (187-203). Cham: Springer. https://doi.org/10.1007/978-3-030-79092-9_9
Standard approaches to developing optimisation algorithms tend to involve selecting an algorithm and tuning it to work well on a large set of problem instances from the domain...
Representation in the (Artificial) Immune System
Journal Article
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...