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...
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...
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...