Review:
Markov Chains
overall review score: 4.5
⭐⭐⭐⭐⭐
score is between 0 and 5
Markov chains are mathematical systems that undergo transitions from one state to another according to certain probabilistic rules. They are used in various fields including probability theory, statistics, economics, and computer science.
Key Features
- States
- Transitions
- Transition probabilities
- Initial state
- Stationary distribution
Pros
- Versatile application in various disciplines
- Ability to model complex systems
- Useful for predicting future states based on current state
Cons
- Sensitivity to initial conditions and transition probabilities
- Assumption of memorylessness may not always hold true in real-world scenarios