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 22 - Reinforcement Learning: Uninformed Combinatorial Search, Q-Learning
VIDEO

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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