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...
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...
Artificial Immune System driven evolution in Swarm Chemistry.
Conference Proceeding
Capodieci, N., Hart, E., & Cabri, G. (2014)
Artificial Immune System driven evolution in Swarm Chemistry. In Proceedings of IEEE SASO 2014, (40-49). https://doi.org/10.1109/SASO.2014.16
Morphogenetic engineering represents an interesting field in which models, frameworks and algorithms can be tested in order to study how self-* properties and emergent behavio...
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...
Hybridisation of Evolutionary Algorithms through hyper-heuristics for global continuous optimisation
Conference Proceeding
Segredo, E., Lalla-Ruiz, E., Hart, E., Paechter, B., & Voß, S. (2016)
Hybridisation of Evolutionary Algorithms through hyper-heuristics for global continuous optimisation. In P. Festa, M. Sellmann, & J. Vanschoren (Eds.), Learning and Intelligent Optimization: 10th International Conference, LION 10, Ischia, Italy, May 29 -- June 1, 2016 (296-305). https://doi.org/10.1007/978-3-319-50349-3_25
Choosing the correct algorithm to solve a problem still remains an issue 40 years after the Algorithm Selection Problem was first posed. Here we propose a hyper-heuristic whic...
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...
Algorithm selection using deep learning without feature extraction
Conference Proceeding
Alissa, M., Sim, K., & Hart, E. (2019)
Algorithm selection using deep learning without feature extraction. In GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion. , (198-206). https://doi.org/10.1145/3321707.3321845
We propose a novel technique for algorithm-selection which adopts a deep-learning approach, specifically a Recurrent-Neural Network with Long-Short-Term-Memory (RNN-LSTM). In ...
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...
A novel similarity-based mutant vector generation strategy for differential evolution
Conference Proceeding
Segredo, E., Lalla-Ruiz, E., & Hart, E. (2018)
A novel similarity-based mutant vector generation strategy for differential evolution. In H. Aguirre (Ed.), Proceedings of the Genetic and Evolutionary Computation Conference 2018https://doi.org/10.1145/3205455.3205628
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...
A Novel Heuristic Generator for JSSP Using a Tree-Based Representation of Dispatching Rules
Conference Proceeding
Sim, K., & Hart, E. (2015)
A Novel Heuristic Generator for JSSP Using a Tree-Based Representation of Dispatching Rules. In GECCO Companion '15 Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation, (1485-1486). https://doi.org/10.1145/2739482.2764697
A previously described hyper-heuristic framework named
NELLI is adapted for the classic Job Shop Scheduling Problem (JSSP) and used to find ensembles of reusable heuristics th...