데블스캠프2017/강화학습으로컴퓨터에게고전게임플레이시키기 (rev. 1.50)
1. machine learning ¶
- Supervised learning
- Unsupervised learning
- Reinforcement learning
1.1. supervised learning ¶
- 학습을 시킬 때 input으로 value와 label을 함께 전달
- Learning from difference between prediction and target
- e.g. mnist, classification
1.2. unsupervised learning ¶
- input: value만 입력, projection등으로 전처리한 값들로 계산
- Cluster by distance between inputs
- Human can't predict the outcome
- e.g. clustering
1.3. reinforcement learning ¶
- 일종의 unsupervised learning
- input : environment, reward, output : action
- Learn from try
- Model free
- e.g. game play, stock trading
1.4. reinforcement learning ¶
- Q learning
- Q learning + Neural Network
- DQN : Deep Q Learning
- hidden layer를 늘리는게 다가 아니다!
1.5. Basic knowledge ¶
- MDP : Markov Decision Process
- Bellman equation
- Dynamic programming
- Value, Polish
- Value function, Polish function
- Value iteration, Polish iteration
