160 citations · 274 across the 23 of their papers we have counts for
4 papers · 1 filter
Generalizing distribution of partial rewards for multi-armed bandits with temporally-partitioned rewards
Ronald C. van den Broek, Rik Litjens, Tobias Sagis +3
We investigate the Multi-Armed Bandit problem with Temporally-Partitioned Rewards (TP-MAB) setting in this paper. In the TP-MAB setting, an agent will receive subsets of the reward…
An Empirical Evaluation of Posterior Sampling for Constrained Reinforcement Learning
Danil Provodin, Pratik Gajane, Mykola Pechenizkiy +1
We study a posterior sampling approach to efficient exploration in constrained reinforcement learning. Alternatively to existing algorithms, we propose two simple algorithms that a…
Survey on Fair Reinforcement Learning: Theory and Practice
Pratik Gajane, Akrati Saxena, Maryam Tavakol +2
Fairness-aware learning aims at satisfying various fairness constraints in addition to the usual performance criteria via data-driven machine learning techniques. Most of the resea…
The Impact of Batch Learning in Stochastic Linear Bandits
Danil Provodin, Pratik Gajane, Mykola Pechenizkiy +1
We consider a special case of bandit problems, named batched bandits, in which an agent observes batches of responses over a certain time period. Unlike previous work, we consider…