Understanding Environmental Influence in an Open-Ended Evolutionary Algorithm
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...
Idiotypic networks for evolutionary controllers in virtual creatures.
Capodieci, N., Hart, E., & Cabri, G. (2014)
Idiotypic networks for evolutionary controllers in virtual creatures. In H. Sayama, J. Rieffel, S. Risi, R. Doursat, & H. Lipson (Eds.), Artificial Life 14: Proceedings of ALife, 14th International Conference on the Synthesis and Simulation of Living Systems, (192-199). https://doi.org/10.7551/978-0-262-32621-6-ch032
We propose a novel method for evolving adaptive locomotive strategies for virtual limbless creatures that addresses both functional and non-functional requirements, respective...
Can justice be fair when it is blind? How social network structures can promote or prevent the evolution of despotism
Perret, C., Powers, S. T., Pitt, J., & Hart, E. (2018)
Can justice be fair when it is blind? How social network structures can promote or prevent the evolution of despotism. In T. Ikegami, N. Virgo, O. Witkowski, M. Oka, R. Suzuki, & H. Iizuka (Eds.), Proceedings of the 2018 Conference on Artificial Lifehttps://doi.org/10.1162/isal_a_00058
Hierarchy is an efficient way for a group to organize, but often goes along with inequality that benefits leaders. To control despotic behaviour, followers can assess leaders'...
A Novel Heuristic Generator for JSSP Using a Tree-Based Representation of Dispatching Rules
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...
A local search for the timetabling problem.
Rossi-Doria, O., Blum, C., Knowles, J., Sampels, M., Socha, K., & Paechter, B. (2001)
A local search for the timetabling problem. In E. Burke, & P. Causmaecker (Eds.), Proceedings of the Conference on the Practice and Theory of Automated Timetabling (PATAT 2002), 124-127
This work is part of the Metaheuristic Network, a European Commission project that seeks to empirically compare the performance of various metaheuristics on different combinat...
Comparing Multi-label Classification with Reinforcement Learning for Summarisation of Time-series Data
Gkatzia, D., Hastie, H., & Lemon, O. (2014)
Comparing Multi-label Classification with Reinforcement Learning for Summarisation of Time-series Data. In Proceedings of the Conference Volume 1: Long Papers. , (1231-1240). https://doi.org/10.3115/v1/p14-1116
We present a novel approach for automatic report generation from time-series data, in the context of student feedback generation. Our proposed methodology treats content selec...
Analysing the performance of migrating birds optimisation approaches for large scale continuous problems
Lalla-Ruiz, E., Segredo, E., Voss, S., Hart, E., & Paechter, B. (2016)
Analysing the performance of migrating birds optimisation approaches for large scale continuous problems. In Parallel Problem Solving from Nature – PPSN XIV. , (134-144). https://doi.org/10.1007/978-3-319-45823-6_13
We present novel algorithmic schemes for dealing with large scale continuous problems. They are based on the recently proposed population-based meta-heuristics Migrating Birds...
Solving CSPs with evolutionary algorithms using self-adaptive constraint weights.
Eiben, A. E., Jansen, B., Michalewicz, Z., & Paechter, B. (2000)
Solving CSPs with evolutionary algorithms using self-adaptive constraint weights. In D. Whitley (Ed.), GECCO-2000 : proceedings of the genetic and evolutionary computation conference, 128-134
This paper examines evolutionary algorithms (EAs) extended by various penalty-based approaches to solve constraint satisfaction
problems (CSPs). In some approaches, the penalt...
An investigation of environmental influence on the benefits of adaptation mechanisms in evolutionary swarm robotics
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 Computation Conference. , (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...
Simulating Dynamic Vehicle Routing Problems with Athos
Hoffman, B., Guckert, M., Chalmers, K., & Urquhart, N. (2019)
Simulating Dynamic Vehicle Routing Problems with Athos. In Proceedings of the 33rd International ECMS Conference on Modelling and Simulation ECMS 2019, (296-302). https://doi.org/10.7148/2019-0296
Complex routing problems, such as vehicle routing problems with additional constraints, are both hard to solve and hard to express in a form that is accessible to the human ex...