DeepLearning
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CS5001
Lectures for the weeks of:
2018-10-15
Probability, Markov chains
- Reading:
- Chapter 8, ArtInt: https://artint.info/2e/html/ArtInt2e.Ch8.html
- Slides:
2018-10-22
Rationality, utility, decisions
- Reading:
- Chapter 9, ArtInt: https://artint.info/2e/html/ArtInt2e.Ch9.html
- Sildes:
- Code: https://artint.info/AIPython/aipython.pdf (explained here)
- Visualizations:
2018-10-29
Reinforcement learning (RL)
- Slides:
- Reading:
- Chapter 12 (skip 10, 11): https://artint.info/2e/html/ArtInt2e.Ch12.html
- ./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:
Extras
Neural nets (NN)
- Code: https://artint.info/AIPython/aipython.pdf (explained here)
- https://artint.info/AIPython/aipython/learnNN.py (not simple enough...)
- More coming soon!
- Slides:
- Reading:
- Chapter 7 ArtInt
- ./NN_reading_extras.tar.gz (read rougly in order of numbering)
Backlinks: index:Classes