activity
20122023
most citedCompositional Planning Using Optimal Option Models

31 citations · 58 across the 5 of their papers we have counts for

collaborators

5 papers

stat.ML20237 cited

Automatic Music Playlist Generation via Simulation-based Reinforcement Learning

Federico Tomasi, Joseph Cauteruccio, Surya Kanoria +3

Personalization of playlists is a common feature in music streaming services, but conventional techniques, such as collaborative filtering, rely on explicit assumptions regarding c…

cs.LG202314 cited

Impatient Bandits: Optimizing Recommendations for the Long-Term Without Delay

Thomas M. McDonald, Lucas Maystre, Mounia Lalmas +2

Recommender systems are a ubiquitous feature of online platforms. Increasingly, they are explicitly tasked with increasing users' long-term satisfaction. In this context, we study…

cs.LG2023

A Strong Baseline for Batch Imitation Learning

Matthew Smith, Lucas Maystre, Zhenwen Dai +1

Imitation of expert behaviour is a highly desirable and safe approach to the problem of sequential decision making. We provide an easy-to-implement, novel algorithm for imitation l…

cs.AI20156 cited

Value Iteration with Options and State Aggregation

Kamil Ciosek, David Silver

This paper presents a way of solving Markov Decision Processes that combines state abstraction and temporal abstraction. Specifically, we combine state aggregation with the options…

cs.AI201231 cited

Compositional Planning Using Optimal Option Models

David Silver, Kamil Ciosek

In this paper we introduce a framework for option model composition. Option models are temporal abstractions that, like macro-operators in classical planning, jump directly from a…