The Multi-Armed Bandit Problem and Its Solutions
Lilian Weng
The multi-armed bandit problem describes an algorithmic dilemma where systems must balance between exploiting known good options and exploring potentially better alternatives. Implementations exist for Bernoulli bandits in the lilianweng/multi-armed-bandit repository. This trade-off applies to real-world scenarios from restaurant selection to ad recommendation systems.
Why it matters
The algorithms are implemented for Bernoulli bandit in lilianweng/multi-armed-bandit. Exploitation vs Exploration The exploration vs exploitation dilemma exists in many aspects of our life. Say, your favorite restaurant is right around the corner. If you go there every day, you would be confident of what you will get, but miss the chances of discovering an even better option. If you try new places all the time, very likely you are gonna have to eat unpleasant food from time to time. Similarly, online advisors try to balance between the known most attractive ads and the new ads that might be even more successful.
