Artificial Intelligence Course, WS 14/15, U Stuttgart


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Scope
We will cover, with slight modifications, the classical course on AI by Stuart Russell, following the AIMA book. See the 00-orga slides for an overview.
Organization
  • This is the central website of the lecture. Link to slides, exercise sheets, announcements, etc will all be posted here.
  • See the 00-orga slides for further information.
Tutorials
  • The Git book is the source for any question regarding git. You basically need to know the information in chapter 2 (Git basics) and it is very helpful to understand chapter 1.3 (also Git basics). Everything else is not very important for you now.

    Git for Windows Please try SourceTree or, if you've been working with Tortoise/SVN before, Tortoise/git

  • The official Python tutorial is a very good starting point, if you already know something about programming. (For the exercises we will use Python 2.7. As long as we don't use libraries, that need Python 2.7, feel free to use Python 3)
  • The official Python documentation is a comprehensive reference, whenever you will have questions to some build-in modules. For the exercises you can use all build-in modules.
  • If you feel your general programming skills could need some improvement, Learn Python The Hard Way is a good beginner's introduction to python as first programming language.
Exercise results
The results of all groups can be found here: ergebnis.
Schedule, slides & exercises
date topics slides exercises
16.10. Organization & Introduction 00-orga
01-intro
02-agents
20.10. Basic Search Methods 03-search
23.10. Please bring you laptop to the lecture hall, with python 2.7, numpy, and git installed. (For non-linux, try Anaconda.)
link to the tutorial
27.10. Informed Search: A-star 04-Astar
31.10. Constraint Satisfaction Problems 05-CSP
03.11. CSP (cont'd) & Optimization 06-optim
6.11. coding exercise: e01-graphsearch (due on 5.11., 24:00)
Präsenzübungen: e02-treeSearch-exercises
10.11. Logical Agents: Propositional Logic 07-propositionalLogic
13.11. First-Order Logic 08-firstOrderLogic
17.11. First-Order Logic (cont'd) 09-FOLinference
20.11. e03-csp
Präsenzübungen: e04-csp-exercises
24.11. Probabilities 10-probabilities
27.11. Bandits 11-banditsUCT
01.12. Games 12-games
15.12. e05-logic
template solution file
18.12. Graphical Models 13-graphicalModels
08.01. cancelled
12.01. e06-chess
Präsenzübungen: e07-probabilities-exercises
15.01. Graphical Models (cont'd)
19.01. Temporal Models, HMMs 14-dynamicModels
15-speech
22.01. MDPs & RL 15-reinforcementLearning
26.01. e08-naive-bayes
Präsenzübung: e09-HMMs
29.01. MDPs & RL
02.02. MDPs & RL: Exploration 16-RLexploration
05.02. Präsenzübung: e10-MDPandRL
09.02. cancelled
12.02. AI = { Machine Learning, Robotics, Vision, Logic + Probabilities, Decision Theory, ... } overview slide
FINAL SCRIPT (formatted differently)