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...
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...
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...
A Cooperative Learning Approach for the Quadratic Knapsack Problem
Conference Proceeding
Lalla-Ruiz, E., Segredo, E., & Voß, S. (2018)
A Cooperative Learning Approach for the Quadratic Knapsack Problem. In Learning and Intelligent Optimization Conference (LION12). , (31-35). https://doi.org/10.1007/978-3-030-05348-2_3
The Quadratic Knapsack Problem (QKP) is a well-known optimization problem aimed to maximize a quadratic objective function subject to linear capacity constraints. It has sever...
Simulating the actions of commuters using a multi-agent system
Journal Article
Urquhart, N., Powers, S., Wall, Z., Fonzone, A., Ge, J., & Polhill, G. (2019)
Simulating the actions of commuters using a multi-agent system. Journal of Artificial Societies and Social Simulation, 22(2), https://doi.org/10.18564/jasss.4007
The activity of commuting to and from a place of work affects not only those travelling but also wider society through their contribution to congestion and pollution. It is de...
Evolution of Diverse, Manufacturable Robot Body Plans
Conference Proceeding
Buchanan, E., Le Goff, L., Hart, E., Eiben, A. E., De Carlo, M., Li, W., …Tyrrell, A. M. (2020)
Evolution of Diverse, Manufacturable Robot Body Plans. In 2020 IEEE Symposium Series on Computational Intelligence (SSCI) (2132-2139). https://doi.org/10.1109/SSCI47803.2020.9308434
Advances in rapid prototyping have opened up new avenues of research within Evolutionary Robotics in which not only controllers but also the body plans (morphologies) of robot...