This is the repository for the EDAF70 - Tillämpad artificiell intelligens (Applied Artificial Intelligence) course given at Lunds Tekniska Högskola (LTH) during the Spring 2019 term.
The following topics are covered in the lab assignments:
- Minimax adversarial search
- Alpha-beta pruning
- Evaluation functions
- Robot localization
- Hidden Markov Models (HMM)
- Forward filtering
- Machine Learning (ML)
- Linear regression
- Logisitic regression
- Gradient descent
- Linear discriminant functions
- Perceptron algorithm
- Cross validation
- Natural Language Processing (NLP)
Other topics covered in the course lectures and reading material:
- Agents
- Search
- Games
- Probabilistic Representation and Reasoning
- Probabilistic Reasoning Over Time
- Logic and Knowledge Representation
- Planning
- Semantic Technology
- Robotics
- Ethics in AI
Course literature:
- Artificial Intelligence: A Modern Approach, 3/e, by Stuart Russell and Peter Norvig, ISBN-10: 0132071487 or 1292153962.
Other related literature:
- Kevin P. Murphy: Machine Learning, A Probabilistic Perspective. MIT Press, 2012, ISBN: 9780262018029.
- Sebastian Ruder: An overview of gradient descent optimization algorithms. http://arxiv.org/abs/1609.04747.
Lectures:
- P. Nugues' slides, available here
- J. Malec's slides, archived and available via web.archive.org.
- E.A Topp's slides, archived and available via web.archive.org.
Companion code:
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent