Joseph's class notes, in [PDF].
- Lecture 01: [PPT] : Overview; background on neural functioning
- Lecture 02: [PPT] : Neurons; motor control, mirror neurons
- Section notes, week 1: [PDF] [OpenOffice]: Neurons
- Lecture 03: [PPT] : Neural development
- Lecture 04: [PPT] : Connectionist models: basics
- Section notes, week 2: [PDF] [OpenOffice]: Reflexes, neural development, and neural modeling
- Lecture 05: [PPT] : Psychological considerations
- Lecture 06: Brain imaging. We have not yet received these slides
- Section notes, week 3: [PDF] [OpenOffice]
- Lecture 07: [PPT] : Learning: biological and connectionist
- Lecture 08: [PPT] : Backpropagation
- Section notes, week 4: Backpropagation and a little bit of learning [PDF] [OpenOffice]
- Lecture 09: [PPT] : Color vision and language
- Lecture 10: [PPT] : Representations and categories
- Section notes, week 5: [PDF] [OpenOffice] : Color, representations, and categories
- Lecture 11: [PPT] : Categories and Concepts
- Lecture 12: [PPT] Michael Ellsworth's guest lecture on FrameNet
- Section notes, week 6: [PDF] : Linguistics
- Lecture 13: [PPT] : Image schemas, including a story about learning them
- Lecture 14: [PPT] : Regier's model continued, plus review for midterm
- Section notes, week 7: [OpenOffice] [PDF] : Midterm review
- Lecture 15: [PPT] : X-Schemas and Petri Nets. Also see these Petri nets which can be viewed with PIPE2
- Section notes, week 8: [OpenOffice] [PDF] : X-Schemas and Actions (I also went over the midterm; it is not posted here.)
- Lecture 16: [PPT] : Best fit, parameterized actions, and model merging
- Lecture 17: [PPT] : The biology of reinforcement learning
- Section notes, week 9: [OpenOffice] [PDF] : Learning grammars via minimum description length
- Lecture 18: [PPT] : Reinforcement learning
- Lecture 19: [PPT] : Reinforcement learning: algorithms and further biology
- Section notes, week 10: [OpenOffice] [PDF] : Reinforcement learning
- Lecture 20: [PPT] : Event structure metaphor
- Lecture 21: [OpenOffice] [PDF] : Last year's slides on Bayes Nets
- Section notes, week 11: [OpenOffice] [PDF] : Review of metaphor, plus some Bayes Nets and a look at Leon's research
- Lecture 22: the karmaSIM metaphor model
- Lecture 23: [PPT] : Grammars and unification
- Section notes, week 12: [OpenOffice] [PDF] : Parsing and unification
- Lecture 24: notes [PDF] : Nate's presentation ECG
- Lecture 25: part 1 [PDF] part 2 [PPT] : Intro to learning grammars
- Section notes, week 13: [OpenOffice] [PDF] : ECG
- Lecture 26: [PPT] : ECG
- Lecture 27: [PPT] : Learning ECG
- Section notes, week 14: [OpenOffice] [PDF] : ECG Learning
- Final review notes: [OpenOffice] [PDF]
- Lecture 28: [PPT] : Binding problem and review of all material from class