Piecing together the puzzle of pictorial representation: How jigsaw puzzles index metacognitive development
Journal Article
Doherty, M. J., Wimmer, M. C., Gollek, C., Stone, C., & Robinson, E. J. (2021)
Piecing together the puzzle of pictorial representation: How jigsaw puzzles index metacognitive development. Child Development, 92(1), 205-221. https://doi.org/10.1111/cdev.13391
Jigsaw puzzles are ubiquitous developmental toys in Western societies, used here to examine the development of metarepresentation. For jigsaw puzzles this entails understandin...
Towards a unified method to synthesising scenarios and solvers in combinatorial optimisation via graph-based approaches
Thesis
Stone, C. L. Towards a unified method to synthesising scenarios and solvers in combinatorial optimisation via graph-based approaches. (Thesis)
Edinburgh Napier University. Retrieved from http://researchrepository.napier.ac.uk/Output/2707229
Hyper-heuristics is a collection of search methods for selecting, combining and generating heuristics used to solve combinatorial optimisation problems. The primary objective ...
On the Synthesis of Perturbative Heuristics for Multiple Combinatorial Optimisation Domains
Conference Proceeding
Stone, C., Hart, E., & Paechter, B. (2018)
On the Synthesis of Perturbative Heuristics for Multiple Combinatorial Optimisation Domains. In Parallel Problem Solving from Nature – PPSN XV 15th International Conference, Coimbra, Portugal, September 8–12, 2018, Proceedings, Part Ihttps://doi.org/10.1007/978-3-319-99253-2_14
Hyper-heuristic frameworks, although intended to be cross-domain at the highest level, rely on a set of domain-specific low-level heuristics at lower levels. For some domains,...
Automatic Generation of Constructive Heuristics for Multiple Types of Combinatorial Optimisation Problems with Grammatical Evolution and Geometric Graphs
Conference Proceeding
Stone, C., Hart, E., & Paechter, B. (2017)
Automatic Generation of Constructive Heuristics for Multiple Types of Combinatorial Optimisation Problems with Grammatical Evolution and Geometric Graphs. In Applications of Evolutionary Computation, 578-593
In many industrial problem domains, when faced with a combinatorial optimisation problem, a “good enough, quick enough” solution to a problem is often required. Simple heurist...