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 Cross-Domain Method for Generation of Constructive and Perturbative Heuristics
Book Chapter
Stone, C., Hart, E., & Paechter, B. (2021)
A Cross-Domain Method for Generation of Constructive and Perturbative Heuristics. In N. Pillay, & R. Qu (Eds.), Automated Design of Machine Learning and Search Algorithms (91-107). Springer. https://doi.org/10.1007/978-3-030-72069-8_6
Hyper-heuristic frameworks, although intended to be cross-domain at the highest level, usually rely on a set of domain-specific low-level heuristics which exist below the doma...
Towards Autonomous Robot Evolution
Book Chapter
Eiben, A. E., Hart, E., Timmis, J., Tyrrell, A. M., & Winfield, A. F. (2021)
Towards Autonomous Robot Evolution. In A. Cavalcanti, B. Dongol, R. Hierons, J. Timmis, & J. Woodcock (Eds.), Software Engineering for Robotics (29-51). Springer. https://doi.org/10.1007/978-3-030-66494-7_2
We outline a perspective on the future of evolutionary robotics and discuss a long-term vision regarding robots that evolve in the real world. We argue that such systems offer...
Biological Networks
Book Chapter
Hart, E. (2011)
Biological Networks. In M. Gargaud, R. Amils, J. Quintanilla, & H. Irvine (Eds.), Encyclopedia of Astrobiology (179-182). Springer. https://doi.org/10.1007/978-3-642-11274-4_178
Exploiting Collaborations in the Immune System: The Future of Artificial Immune Systems
Book Chapter
Hart, E., McEwan, C., & Davoudani, D. (2009)
Exploiting Collaborations in the Immune System: The Future of Artificial Immune Systems. In C. Mumford, & L. Jain (Eds.), Intelligent Systems Reference Library; Computational Intelligence, 527-558. Springer-Verlag. doi:10.1007/978-3-642-01799-5_16
Despite a steady increase in the application of algorithms inspired by the natural immune system to a variety of domains over the previous decade, we argue that the field of A...
Genetic algorithms and timetabling
Book Chapter
Ross, P., Hart, E., & Corne, D. (2003)
Genetic algorithms and timetabling. In A. Ghosh, & K. Tsutsui (Eds.), Advances in Evolutionary Optimisation. Springer. https://doi.org/10.1007/978-3-642-18965-4_30
Genetic algorithms can be used to search very large spaces, and it would seem natural to use them for tackling the nastier kinds of timetabling problem. We completed an EPSRC-...
Hyper Heuristics: an emerging direction in modern search technology.
Book Chapter
Burke, E., Hart, E., Kendall, G., Newall, J., Ross, P., & Schulenburg, S. (2003)
Hyper Heuristics: an emerging direction in modern search technology. In F. Glover, & G. A. Kochenberger (Eds.), Handbook of MetaHeuristics, 457-474. Springer US. https://doi.org/10.1007/0-306-48056-5_16