Items where authors include "Lissovoi, A."

Article

Lissovoi, A., Oliveto, P.S. and Warwicker, J.A. (2022) When move acceptance selection hyper-heuristics outperform metropolis and elitist evolutionary algorithms and when not. Artificial Intelligence. 103804. ISSN 0004-3702

Corus, D., Lissovoi, A., Oliveto, P. et al. (1 more author) (2021) On steady-state evolutionary algorithms and selective pressure: Why inverse rank-based allocation of reproductive trials is best. ACM Transactions on Evolutionary Learning and Optimization, 1 (1). 2. ISSN 2688-299X

Lissovoi, A., Oliveto, P. and Warwicker, J.A. (2020) Simple hyper-heuristics control the neighbourhood size of randomised local search optimally for LeadingOnes. Evolutionary Computation, 28 (3). pp. 437-461. ISSN 1063-6560

Lissovoi, A. and Oliveto, P.S. (2019) On the time and space complexity of genetic programming for evolving Boolean conjunctions. Journal of Artificial Intelligence Research, 66. pp. 655-689. ISSN 1076-9757

Lissovoi, A. and Witt, C. (2018) The Impact of a sparse migration topology on the runtime of island models in dynamic optimization. Algorithmica, 80 (5). pp. 1634-1657. ISSN 0178-4617

Lissovoi, A. and Witt, C. (2017) A Runtime Analysis of Parallel Evolutionary Algorithms in Dynamic Optimization. Algorithmica, 78 (2). pp. 641-659. ISSN 0178-4617

Book Section

Lissovoi, A. and Oliveto, P.S. (2020) Computational complexity analysis of genetic programming. In: Doerr, B. and Neumann, F., (eds.) Theory of Evolutionary Computation: Recent Developments in Discrete Optimization. Natural Computing Series . Springer Nature Switzerland AG , pp. 475-518. ISBN 9783030294137

Proceedings Paper

Lissovoi, A., Oliveto, P. and Warwicker, J.A. (2020) How the duration of the learning period affects the performance of random gradient selection hyper-heuristics. In: Proceedings of the AAAI Conference on Artificial Intelligence. Thirty-Fourth AAAI Conference on Artificial Intelligence, 07-12 Feb 2020, New York, NY, USA. Association for the Advancement of Artificial Intelligence (AAAI) , pp. 2376-2383.

Doerr, B., Lissovoi, A. and Oliveto, P.S. (2019) Evolving boolean functions with conjunctions and disjunctions via genetic programming. In: GECCO '19 : Proceedings of the Genetic and Evolutionary Computation Conference. The Genetic and Evolutionary Computation Conference - GECCO 2019, 13-17 Jul 2019, Prague, Czech Republic. ACM Digital Library . ISBN 9781450361118

Doerr, B., Lissovoi, A., Oliveto, P.S. et al. (1 more author) (2018) On the runtime analysis of selection hyper-heuristics with adaptive learning periods. In: Aguirre, H.E. and Takadama, K., (eds.) GECCO '18 Proceedings of the Genetic and Evolutionary Computation Conference. GECCO '18 Genetic and Evolutionary Computation Conference, 15-19 Jul 2018, Kyoto, Japan. ACM , pp. 1015-1022. ISBN 978-1-4503-5618-3

Lissovoi, A. and Oliveto, P.S. (2018) On the Time and Space Complexity of Genetic Programming for Evolving Boolean Conjunctions. In: McIlraith, S.A. and Weinberger, K.Q., (eds.) Thirty-Second AAAI Conference on Artificial Intelligence. Thirty-Second AAAI Conference on Artificial Intelligence, 02-07 Feb 2017, New Orleans, Louisiana, USA. Association for the Advancement of Artificial Intelligence .

Lissovoi, A., Oliveto, P.S. and Warwicker, J.A. (2017) On the runtime analysis of generalised selection hyper-heuristics for pseudo-boolean optimisation. In: GECCO 2017: Proceedings of the 2017 Genetic and Evolutionary Computation Conference. GECCO '17 The Genetic and Evolutionary Computation Conference, 15-19 Jul 2017, Berlin, Germany. ACM , pp. 849-856. ISBN 9781450349208

Lissovoi, A., Sudholt, D. orcid.org/0000-0001-6020-1646, Wagner, M. et al. (1 more author) (2017) Theoretical results on bet-and-run as an initialisation strategy. In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2017). Genetic and Evolutionary Computation Conference (GECCO 2017), 15/07/2017 - 19/07/2017, Berlin. ACM , pp. 857-864.