Reinforcement learningHow to find good sequences of decisions in an unknown domain through exploration and learning?Stunning success of AlphaZero using reinforcement learningDelayed rewards, long-term benefits of decisions, exploration and exploitationImproving decision policy through explorationGeneralising what has been learnedMachine learning from noisy dataProblems with noise in learning dataKey ideas to cope with noise: paradoxically, simpler models are often betterAlgorithms for learning decision trees from noisy dataHow to estimate probabilities in machine learning correctly?Argument-Based Machine Learning (ABML)Human expert may help learning by annotating training examples with argumentsAn algorithm for learning rules from argumented examplesABML knowledge-elicitation loopLearning qualitative models with applications in roboticsHow to model qualitatively, avoiding numbersReasoning and simulation with qualitative modelsLearning qualitative models from observations with QUIN and PadeLearning and planning of robot tasks: rescue robot, humanoid robot, quadcopterLearning from examples and background knowledgeHow to use prior knowledge in Machine Learning?Learning in logic – Inductive Logic Programming (ILP)Learning programs from examples with ILPDiscovering problem structure with function decompositionThe idea of structuring the learning problem with function decompositionDiscovering structure with HINT algorithmImproving accuracy and interpretability by structure learning in practice