## Artificial Intelligence

**Artificial Intelligence (Hochschule Ravensburg-Weingarten Univ.)**. Instructor: Professor Wolfgang Ertel. This course provides an overview of the field of Artificial Intelligence (AI)
with its current widespread ramifications. Topics covered in this course include: search, game playing, problem solving; reasoning with Bayesian networks; machine learning and data mining;
neural networks; reinforcement learning. And some of the topics will be dealt with in more detail.

Lecture 01 - Introduction |

Lecture 02 - Search, Games and Problem Solving Introduction |

Lecture 03 - Uninformed Search: Breadth-First Search, Depth-First Search, Iterative Deepening |

Lecture 04 - Heuristic Search: Greedy Search, A*-Search, IDA*-Search |

Lecture 05 - Games with Opponents, Heuristic Evaluation Functions |

Lecture 06 - Computing with Probabilities, The Principle of Maximum Entropy |

Lecture 07 - The Maximum Entropy Method |

Lecture 08 - The Maximum Entropy Method, LEXMED |

Lecture 09 - LEXMED, Reasoning with Bayesian Networks |

Lecture 10 - Reasoning with Bayesian Networks |

Lecture 11 - Reasoning with Bayesian Networks, Machine Learning and Data Mining |

Lecture 12 - The Perceptron, The Nearest Neighbour Method |

Lecture 13 - The Nearest Neighbour Method, Decision Tree Learning |

Lecture 14 - Decision Tree Learning |

Lecture 15 - Decision Tree Learning, Learning of Bayesian Networks |

Lecture 16 - The Naive Bayes Classifier, Clustering |

Lecture 17 - Clustering, Data Mining in Practice |

Lecture 18 - Neural Networks: Modeling Learning, Hopfield Networks, Autoassociative Memory |

Lecture 19 - Neural Networks: Autoassociative Memory |

Lecture 20 - Neural Networks: Linear Networks with Minimal Errors, The Backpropagation Algorithm |

Lecture 21 - Neural Networks: The Backpropagation Algorithm, Support Vector Machines |

Lecture 22 - Reinforcement Learning: Uninformed Combinatorial Search, Q-Learning |

Lecture 23 - Reinforcement Learning: Q-Learning |

Lecture 24 - Reinforcement Learning: Exploration and Exploitation, Curse of Dimensionality |

Lecture 25 - Recommender Systems: The Link-analysis Algorithm, Nearest neighbour Filtering |