Notes for UCB CS 188
1. Intro to AI
AI History
- 1940-1950: Early days: neural and computer science meet
- 1950—70: Excitement! Logic-driven
- 1965: Robinson's complete algorithm for logical reasoning
- 1970—90: Knowledge-based approaches
- 1990—: Statistical approaches
- Agents and learning systems
- Resurgence of probability, focus on uncertainty
- 2000—: Where are we now?
- Big data, big compute, neural networks
Agent
An agent is an entity that perceives and acts 
Course Topics
- Search & Planning
- How can I find a sequence of best decisions for a particular situation?
- Reinforcement Learning
- How can I find rules (policy) to make best decisions for any situation?
- Probability & Inference
- How can I make sense of uncertainty in the world?
- Supervised Learning
- How can I learn a model of the world from data?
2. Uninformed Search
Search Problems
A search problem consists of:
- A state space
- A successor function (with actions, costs)
- A start state and a goal test A solution is a sequence of actions (a plan) which transforms the start state to a goal state
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