Content is my notes based on the materials of Artifical Intelligent course teached by Dr. Meng Cheng Lau of Laurentian University.
Branches of AI
- Expert System
Computer system that emulate decision-making abilities of human expert in certain fields. Example: stock trading. - Planning and Decision Making
Algorithms and techniques that allow machines to plan actions or make decision to archive specific goals. Example: Scheduling - Knowledge Representation and Reasoning
Representing information about the world in a form that a computer system can utilize to solve complex tasks like diagnosis or problem-solving. Example: medical diagnosis - Neural Networks
Architecture inspired by the structure and function of the brain. they consist of interconnected nodes or “neurous” - Machine Learning(ML):- learn from data
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
- Deep Learning
- Natural Language Process(NLP) and Speech Recognization
Focus on the interaction between computers and human languages. Example: translation, sentiment analysis, and chatbots. - Computer Vision
Give machine the ability to interpret and decide based on visual data from the world. Examples: image recognition, facial recognition, and object detection. - Robotics
Deal with construction, operation and use of robots. AI in robotics can include perception, planning, and decision-making. Examples: Roomba, Industrial robots.
broad usage of AI
| Area | Application |
|---|---|
| Healthcare | Pridictive Diagnosis |
| Finance | Fraud detection |
| Entertainment | Game AI, Movie recommendations |
| Transportation | Self-Driving cars |
| Robotics | Intelligent control |
| Art and literacy | LLM, Generative AI(ChatGPT, DALL-E, etc.) |
DFS, BFC, UCS, Greedy, A*
- When will BFS outperform DFS?
- Shallow solutions 浅层搜索
- Cyclics or infinite Graphs 环或者无线图
- When will DFS outperform BFS?
- Space Constraints 存储空间约束
- Need the explore the entire search space 需要查找全部空间