38 citations · 141 across the 22 of their papers we have counts for
24 papers
A General Upper Bound for the Runtime of a Coevolutionary Algorithm on Impartial Combinatorial Games
Alistair Benford, Per Kristian Lehre
Due to their complex dynamics, combinatorial games are a key test case and application for algorithms that train game playing agents. Among those algorithms that train using self-p…
Overcoming Binary Adversarial Optimisation with Competitive Coevolution
Per Kristian Lehre, Shishen Lin
Co-evolutionary algorithms (CoEAs), which pair candidate designs with test cases, are frequently used in adversarial optimisation, particularly for binary test-based problems where…
Concentration Tail-Bound Analysis of Coevolutionary and Bandit Learning Algorithms
Per Kristian Lehre, Shishen Lin
Runtime analysis, as a branch of the theory of AI, studies how the number of iterations algorithms take before finding a solution (its runtime) depends on the design of the algorit…
Non-Elitist Evolutionary Multi-Objective Optimisation: Proof-of-Principle Results
Zimin Liang, Miqing Li, Per Kristian Lehre
Elitism, which constructs the new population by preserving best solutions out of the old population and newly-generated solutions, has been a default way for population update sinc…
Runtime Analysis of Competitive co-Evolutionary Algorithms for Maximin Optimisation of a Bilinear Function
Per Kristian Lehre
Co-evolutionary algorithms have a wide range of applications, such as in hardware design, evolution of strategies for board games, and patching software bugs. However, these algori…
Self-adaptation in non-Elitist Evolutionary Algorithms on Discrete Problems with Unknown Structure
Brendan Case, Per Kristian Lehre
A key challenge to make effective use of evolutionary algorithms is to choose appropriate settings for their parameters. However, the appropriate parameter setting generally depend…