Conference Paper (published)
Towards explaining metaheuristic solution quality by data mining surrogate fitness models for importance of variables
Wallace A, Brownlee AEI & Cairns D (2021) Towards explaining metaheuristic solution quality by data mining surrogate fitness models for importance of variables. In: Bramer M & Ellis R (eds.) Artificial Intelligence XXXVIII. Lecture Notes in Computer Science, 13101. 41st SGAI International Conference on Artificial Intelligence, AI 2021, Cambridge, 14.12.2021-16.12.2021. Cham, Switzerland: Springer, pp. 58-72. https://doi.org/10.1007/978-3-030-91100-3_5
Conference Paper (published)
Mining Markov Network Surrogates to Explain the Results of Metaheuristic Optimisation
Brownlee A, Wallace A & Cairns D (2021) Mining Markov Network Surrogates to Explain the Results of Metaheuristic Optimisation. In: Martin K, Wiratunga N & Wijekoon A (eds.) Proceedings of the SICSA eXplainable Artifical Intelligence Workshop 2021. CEUR Workshop Proceedings, 2894. SICSA eXplainable Artifical Intelligence Workshop 2021, Aberdeen, 01.06.2021-01.06.2021. Aachen: CEUR Workshop Proceedings, pp. 64-70. http://ceur-ws.org/Vol-2894/short9.pdf