11 citations · 11 across the 7 of their papers we have counts for
4 papers · 1 filter
A Fresh Look at Lamarckian Evolution and the Baldwin Effect
Inès Benito, Johannes F. Lutzeyer, Benjamin Doerr
Baldwinian and Lamarckian evolution have existed for a long time in evolutionary algorithms (EAs) without ever dominating the academic literature or practical applications. In this…
Speeding Up Hyper-Heuristics With Markov-Chain Operator Selection and the Only-Worsening Acceptance Operator
Abderrahim Bendahi, Benjamin Doerr, Adrien Fradin +1
The move-acceptance hyper-heuristic was recently shown to be able to leave local optima with astonishing efficiency (Lissovoi et al., Artificial Intelligence (2023)). In this work,…
Hyper-Heuristics Can Profit From Global Variation Operators
Benjamin Doerr, Johannes F. Lutzeyer
In recent work, Lissovoi, Oliveto, and Warwicker (Artificial Intelligence (2023)) proved that the Move Acceptance Hyper-Heuristic (MAHH) leaves the local optimum of the multimodal…
How the Move Acceptance Hyper-Heuristic Copes With Local Optima: Drastic Differences Between Jumps and Cliffs
Benjamin Doerr, Arthur Dremaux, Johannes Lutzeyer +1
In recent work, Lissovoi, Oliveto, and Warwicker (Artificial Intelligence (2023)) proved that the Move Acceptance Hyper-Heuristic (MAHH) leaves the local optimum of the multimodal…