A hyper-heuristic performs search over a set of other search mechanisms. During the search, it does not require any problem-dependent data. This structure makes hyperheuristics pro...
Mustafa Misir, Katja Verbeeck, Patrick De Causmaec...
Abstract— Meta-learning helps us find solutions to computational intelligence (CI) challenges in automated way. Metalearning algorithm presented in this paper is universal and m...
Learning Bayesian network structure from large-scale data sets, without any expertspecified ordering of variables, remains a difficult problem. We propose systematic improvements ...
Bayesian inference is an appealing approach for leveraging prior knowledge in reinforcement learning (RL). In this paper we describe an algorithm for discovering different classes...
— Visible Past proposes a new class of interdisciplinary learning, documenting, knowledge production, and discovery experiences that are anchored in space and time indicators. Th...