https://github.com/hanzopgp/modernapproachaiexercices
Artificial Intelligence A Modern Approach 4th edition exercices.
https://github.com/hanzopgp/modernapproachaiexercices
artificial-intelligence computer-vision constraint-satisfaction-problem deep-learning machine-learning natural-language-processing personal reinforcement-learning
Last synced: 4 months ago
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Artificial Intelligence A Modern Approach 4th edition exercices.
- Host: GitHub
- URL: https://github.com/hanzopgp/modernapproachaiexercices
- Owner: hanzopgp
- Created: 2021-05-28T20:39:29.000Z (about 4 years ago)
- Default Branch: master
- Last Pushed: 2022-11-09T16:19:11.000Z (over 2 years ago)
- Last Synced: 2025-01-16T05:25:08.020Z (5 months ago)
- Topics: artificial-intelligence, computer-vision, constraint-satisfaction-problem, deep-learning, machine-learning, natural-language-processing, personal, reinforcement-learning
- Homepage:
- Size: 501 KB
- Stars: 31
- Watchers: 4
- Forks: 10
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
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README
# Presentation
>Exercices from the book Artificial Intelligence : A Modern Approach 4th edition. I'm currently reading this book and I will be pushing the exercices in each chapter once I finish. There is 28 chapters in the book and roughly 20 exercices per chapters.
ModernApproachAIExercices/
├── exercices/
│ ├── 1_Artificial_Intelligence/
│ │ ├── 1_Introduction/
│ │ └── 2_Intelligent_Agent/
│ ├── 2_Problem-solving/
│ │ ├── 3_Solving_Problems_By_Searching/
│ │ ├── 4_Beyond_Classical_Search/
│ │ ├── 5_Adversarial_Search/
│ │ └── 6_Constraint_Satisfaction_Problems/
│ ├── 3_Knowledge_reasoning_planning/
│ ├── 4_Uncertain_knowledge_reasoning/
│ ├── 5_Learning/
│ │ ├── 18_Learning_From_Examples/
│ │ ├── 19_Knowledge_In_Learning/
│ │ ├── 20_Learning_Probabilistic_Models/
│ │ └── 21_Reinforcement_Learning
│ ├── 6_Communicating_perceiving_and_acting/
│ │ ├── 22_Natural_Language_Processing/
│ │ └── 23_Natural_Language_For_Communication/
│ └── 7_Conclusions/
└── README.md
# Book's chapter
Part I: Artificial Intelligence
Chapter 1 - Introduction ... 1
Chapter 2 - Intelligent Agents ... 36
Part II: Problem-solving
Chapter 3 - Solving Problems by Searching ... 63
Chapter 4 - Search in Complex Environments ... 110
Chapter 5 - Adversarial Search and Games ... 146
Chapter 6 - Constraint Satisfaction Problems ... 180
Part III: Knowledge, reasoning, and planning
Chapter 7 - Logical Agents ... 208
Chapter 8 - First-Order Logic ... 251
Chapter 9 - Inference in First-Order Logic ... 280
Chapter 10 - Knowledge Representation ... 314
Chapter 11 - Automated Planning ... 344
Part IV: Uncertain knowledge and reasoning
Chapter 12 - Quantifying Uncertainty ... 385
Chapter 13 - Probabilistic Reasoning ... 412
Chapter 14 - Probabilistic Reasoning over Time ... 461
Chapter 15 - Probabilistic Programming ... 500
Chapter 16 - Making Simple Decisions ... 528
Chapter 17 - Making Complex Decisions ... 562
Chapter 18 - Multiagent Decision Making ... 599
Part V: Machine Learning
Chapter 19 - Learning from Examples ... 651
Chapter 20 - Learning Probabilistic Models ... 721
Chapter 21 - Deep Learning ... 750
Chapter 22 - Reinforcement Learning ... 789
Part VI: Communicating, perceiving, and acting
Chapter 23 - Natural Language Processing ... 823
Chapter 24 - Deep Learning for Natural Language Processing ... 856
Chapter 25 - Computer Vision ... 881
Chapter 26 - Robotics ... 925
Part VII: Conclusions
Chapter 27 - Philosophy, Ethics, and Safety of AI ... 981
Chapter 28 - The Future of AI ... 1012
# Links
- Book : https://www.pearson.com/us/higher-education/program/Russell-Artificial-Intelligence-A-Modern-Approach-4th-Edition/PGM1263338.html
- Exercices : https://aimacode.github.io/aima-exercises/
- Resources : http://aima.cs.berkeley.edu/