DeepAI AI Chat
Log In Sign Up

Incentivizing Combinatorial Bandit Exploration

by   Xinyan Hu, et al.

Consider a bandit algorithm that recommends actions to self-interested users in a recommendation system. The users are free to choose other actions and need to be incentivized to follow the algorithm's recommendations. While the users prefer to exploit, the algorithm can incentivize them to explore by leveraging the information collected from the previous users. All published work on this problem, known as incentivized exploration, focuses on small, unstructured action sets and mainly targets the case when the users' beliefs are independent across actions. However, realistic exploration problems often feature large, structured action sets and highly correlated beliefs. We focus on a paradigmatic exploration problem with structure: combinatorial semi-bandits. We prove that Thompson Sampling, when applied to combinatorial semi-bandits, is incentive-compatible when initialized with a sufficient number of samples of each arm (where this number is determined in advance by the Bayesian prior). Moreover, we design incentive-compatible algorithms for collecting the initial samples.


page 1

page 2

page 3

page 4


Efficient Pure Exploration for Combinatorial Bandits with Semi-Bandit Feedback

Combinatorial bandits with semi-bandit feedback generalize multi-armed b...

Sample Complexity of Incentivized Exploration

We consider incentivized exploration: a version of multi-armed bandits w...

Optimal Algorithm for Bayesian Incentive-Compatible

We consider a social planner faced with a stream of myopic selfish agent...

Fiduciary Bandits

Recommendation systems often face exploration-exploitation tradeoffs: th...

Conservative Exploration using Interleaving

In many practical problems, a learning agent may want to learn the best ...

Recommendation Systems and Self Motivated Users

Modern recommendation systems rely on the wisdom of the crowd to learn t...

Recommending Paths: Follow or Not Follow?

Mobile social network applications constitute an important platform for ...