# 1 DeepLearning

## 1.2 Lectures for the weeks of:

### 1.2.1 2018-10-15

#### 1.2.1.1 Probability, Markov chains

• Chapter 8, ArtInt: https://artint.info/2e/html/ArtInt2e.Ch8.html
• Slides:

### 1.2.2 2018-10-22

#### 1.2.2.1 Rationality, utility, decisions

• Chapter 9, ArtInt: https://artint.info/2e/html/ArtInt2e.Ch9.html
• Sildes:
• Code: https://artint.info/AIPython/aipython.pdf (explained here)
• https://artint.info/AIPython/aipython/mdpProblem.py
• https://artint.info/AIPython/aipython/mdpExamples.py
• Visualizations:

### 1.2.3 2018-10-29

#### 1.2.3.1 Reinforcement learning (RL)

• Slides:
• Chapter 12 (skip 10, 11): https://artint.info/2e/html/ArtInt2e.Ch12.html
• DeepLearning/RL_survey_Kaelbling1996.pdf
• http://www.scholarpedia.org/article/Reinforcement_learning
• http://www.scholarpedia.org/article/Temporal_difference_learning
• https://en.wikipedia.org/wiki/Reinforcement_learning
• https://en.wikipedia.org/wiki/Q-learning
• https://en.wikipedia.org/wiki/State%E2%80%93action%E2%80%93reward%E2%80%93state%E2%80%93action
• Visualizations:
• Code: https://artint.info/AIPython/aipython.pdf (explained here)
• https://artint.info/AIPython/aipython/rlProblem.py
• https://artint.info/AIPython/aipython/rlSimpleEnv.py
• https://artint.info/AIPython/aipython/rlQLearner.py
• https://artint.info/AIPython/aipython/rlModelLearner.py
• https://artint.info/AIPython/aipython/rlFeatures.py
• https://artint.info/AIPython/aipython/rlSimpleGameFeatures.py
• https://artint.info/AIPython/aipython/rlPlot.py
• Assignment:

## 1.3 Extras

#### 1.3.0.1 Neural nets (NN)

• Code: https://artint.info/AIPython/aipython.pdf (explained here)
• https://artint.info/AIPython/aipython/learnNN.py (not simple enoughâ€¦)
• More coming soon!
• Slides: