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https://github.com/mhahsler/cs7320-ai
Examples for an AI course following the textbook Artificial Intelligence: A Modern Approach by Russell and Norvig.
https://github.com/mhahsler/cs7320-ai
ai educational jupyter-notebook machine-learning python
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Examples for an AI course following the textbook Artificial Intelligence: A Modern Approach by Russell and Norvig.
- Host: GitHub
- URL: https://github.com/mhahsler/cs7320-ai
- Owner: mhahsler
- License: cc-by-sa-4.0
- Created: 2020-08-19T16:07:51.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2024-12-17T17:22:26.000Z (24 days ago)
- Last Synced: 2025-01-03T22:12:03.745Z (7 days ago)
- Topics: ai, educational, jupyter-notebook, machine-learning, python
- Language: HTML
- Homepage:
- Size: 486 MB
- Stars: 60
- Watchers: 8
- Forks: 152
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.txt
Awesome Lists containing this project
README
# Artificial Intelligence - Lecture Material, Simple Python Code Examples and Assignments
Lecture material, simple Python code examples, and assignments for the course
CS 5/7320 Artificial Intelligence taught
by [Michael Hahsler](https://michael.hahsler.net/)
at the
[Department of Computer Science at SMU](https://www.smu.edu/Lyle/Academics/Departments/CS).
The code examples cover several chapters of the textbook [Artificial Intelligence: A Modern Approach (AIMA)](http://aima.cs.berkeley.edu/) by Russell and Norvig. The code in this repository is intended to be simple to focus more on the basic AI concepts and less on the use of advanced implementation techniques (e.g., object-oriented design and flexibility).
More complex code examples accompanying the textbook can be found at the [GitHub repository aimacode](https://github.com/aimacode).
## Covered AIMA Chapters
| Chapter | Lecture Slides | Code |
| :-------| :----: | :--: |
| 1: Introduction to AI (+ 27 Ethics and Safety) | [PDF](https://mhahsler.github.io/CS7320-AI/slides/01_intro.pdf), [PowerPoint](https://mhahsler.github.io/CS7320-AI/slides/01_intro.pptx) | - |
| 2: Intelligent Agents | [PDF](https://mhahsler.github.io/CS7320-AI/slides/02_agents.pptx), [PowerPoint](https://mhahsler.github.io/CS7320-AI/slides/02_agents.pdf) | [Code](Agents) |
| 3: Solving Problems by Search | [PDF](https://mhahsler.github.io/CS7320-AI/slides/03_search.pdf), [PowerPoint](https://mhahsler.github.io/CS7320-AI/slides/03_search.pptx) | [Code](Search) |
| 4.1-4.2: Search in Complex Environments: Local Search | [PDF](https://mhahsler.github.io/CS7320-AI/slides/04_local_search.pdf), [PowerPoint](https://mhahsler.github.io/CS7320-AI/slides/04_local_search.pptx) | [Code](Local_Search) |
| 4.3-4.5: Search in Complex Environments: Search with Uncertainty | [PDF](https://mhahsler.github.io/CS7320-AI/slides/04_search_with_uncertainty.pdf), [PowerPoint](https://mhahsler.github.io/CS7320-AI/slides/04_search_with_uncertainty.pptx) | [Code](Games) |
| 5: Adversarial Search and Games | [PDF](https://mhahsler.github.io/CS7320-AI/slides/05_games.pdf), [PowerPoint](https://mhahsler.github.io/CS7320-AI/slides/05_games.pptx) | [Code](Games) |
| 6: Constraint Satisfaction Problem | [PDF](https://mhahsler.github.io/CS7320-AI/slides/06_CSP.pdf), [PowerPoint](https://mhahsler.github.io/CS7320-AI/slides/06_CSP.pptx) | [Code](CSP) |
| 7-10: Knowledge-Based Agents | [PDF](https://mhahsler.github.io/CS7320-AI/slides/07_knowledge-based.pdf), [PowerPoint](https://mhahsler.github.io/CS7320-AI/slides/07_knowledge-based.pptx) | [Code](Knowledge-based) |
| 11: Automated Planning| [PDF](https://mhahsler.github.io/CS7320-AI/slides/11_Automated_Planning.pdf), [PowerPoint](https://mhahsler.github.io/CS7320-AI/slides/11_Automated_Planning.pptx) | - |
| 12: Quantifying Uncertainty | [PDF](https://mhahsler.github.io/CS7320-AI/slides/12_uncertainty.pdf),[PowerPoint](https://mhahsler.github.io/CS7320-AI/slides/12_uncertainty.pptx) | [Code](Uncertainty) |
| 13: Probabilistic Reasoning | [PDF](https://mhahsler.github.io/CS7320-AI/slides/13_bayes_nets.pdf), [PowerPoint](https://mhahsler.github.io/CS7320-AI/slides/13_bayes_nets.pptx) | [Code](Probabilistic_Reasoning) |
| 16: Making Simple Decision | [PDF](https://mhahsler.github.io/CS7320-AI/slides/16_decision_making.pdf), [PowerPoint](https://mhahsler.github.io/CS7320-AI/slides/16_decision_making.pptx) | - |
| 19: Learning from Examples (Machine Learning) | [PDF](https://mhahsler.github.io/CS7320-AI/slides/19_ML_intro.pdf), [PowerPoint](https://mhahsler.github.io/CS7320-AI/slides/19_ML_intro.pptx) | [Code](ML) |
| 22+17: Reinforcement Learning and MDPs | [PDF](https://mhahsler.github.io/CS7320-AI/slides/22_Reinforcement_Learning.pdf), [PowerPoint](https://mhahsler.github.io/CS7320-AI/slides/22_Reinforcement_Learning.pptx) | [Code](RL) |
 [Ask the AIMA Scholar (GPT)](https://chatgpt.com/g/g-pNvaqyjSZ-aima-scholar) a question about the content of the textbook.
## HOWTOs
* [HOWTO install and use Python and Jupyter Notebooks](HOWTOs/tools.md)
* [HOWTO work on assignments](HOWTOs/working_on_assignments.md)
* [HOWTOs for AI with Python with code examples](HOWTOs)
## License
All code and documents in this repository are provided under [Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) License.](https://creativecommons.org/licenses/by-sa/4.0/)
