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On the Time and Space Complexity of Genetic Programming for Evolving Boolean Conjunctions., and . AAAI, page 1363-1370. AAAI Press, (2018)Computational Complexity Analysis of Genetic Programming., and . Theory of Evolutionary Computation, Springer, (2020)Evolving boolean functions with conjunctions and disjunctions via genetic programming., , and . GECCO, page 1003-1011. ACM, (2019)On the Time Complexity of Algorithm Selection Hyper-Heuristics for Multimodal Optimisation., , and . AAAI, page 2322-2329. AAAI Press, (2019)On the runtime analysis of selection hyper-heuristics with adaptive learning periods., , , and . GECCO, page 1015-1022. ACM, (2018)Simple Hyper-Heuristics Control the Neighbourhood Size of Randomised Local Search Optimally for LeadingOnes*., , and . Evol. Comput., 28 (3): 437-461 (2020)When move acceptance selection hyper-heuristics outperform Metropolis and elitist evolutionary algorithms and when not., , and . Artif. Intell., (2023)(1+1) Genetic Programming With Functionally Complete Instruction Sets Can Evolve Boolean Conjunctions and Disjunctions with Arbitrarily Small Error., , and . CoRR, (2023)Hyper-heuristics Can Achieve Optimal Performance for Pseudo-Boolean Optimisation., , and . CoRR, (2018)On the runtime analysis of generalised selection hyper-heuristics for pseudo-boolean optimisation., , and . GECCO, page 849-856. ACM, (2017)