mlsanityData to 7 Oct 2026

Causal Bandits: Learning Good Interventions via Causal Inference

arXiv 1606.03203 ↗First posted 10 Jun 2016stat.ML cs.LGcited by 100

Not on the map. Why?

Abstract (arXiv)

We study the problem of using causal models to improve the rate at which good interventions can be learned online in a stochastic environment. Our formalism combines multi-arm bandits and causal inference to model a novel type of bandit feedback that is not exploited by existing approaches. We propose a new algorithm that exploits the causal feedback and prove a bound on its simple regret that is strictly better (in all quantities) than algorithms that do not use the additional causal information.

Key facts. Cited by 100 papers in the map (data through 7 Oct 2026). First posted on arXiv 10 Jun 2016.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 15; 2022: 18; 2023: 22; 2024: 18; 2025: 15; 2026: 12.

100 papers.

Sort:

By area:

  1. 2022Causal Structure Learning: a Combinatorial Perspectivecited by 46
  2. 2023A Survey on Causal Reinforcement Learningcited by 43
  3. 2021Causal Bandits with Unknown Graph Structurecited by 37
  4. 2022Active Learning for Optimal Intervention Design in Causal Modelscited by 30
  5. 2022Model-based Causal Bayesian Optimizationcited by 26
  6. 2023Designing Decision Support Systems Using Counterfactual Prediction Setscited by 26
  7. 2022Hindsight Learning for MDPs with Exogenous Inputscited by 25
  8. 2022Revisiting Simple Regret: Fast Rates for Returning a Good Armcited by 25
  9. 2022Evaluation Methods and Measures for Causal Learning Algorithmscited by 23
  10. 2023Causal Reinforcement Learning: A Surveycited by 22
  11. 2023Causal Deep Learningcited by 20
  12. 2022Causal Bandits for Linear Structural Equation Modelscited by 19
38 more
  1. 2022Adaptively Exploiting d-Separators with Causal Banditscited by 18
  2. 2021Invariant Policy Learning: A Causal Perspectivecited by 17
  3. 2021Dynamic Causal Bayesian Optimizationcited by 17
  4. 2022Fairness and Welfare Quantification for Regret in Multi-Armed Banditscited by 17
  5. 2021Matching a Desired Causal State via Shift Interventionscited by 16
  6. 2022Combinatorial Causal Banditscited by 16
  7. 2021A Causal Bandit Approach to Learning Good Atomic Interventions in Presence of Unobserved Confounderscited by 15
  8. 2021Achieving Counterfactual Fairness for Causal Banditcited by 15
  9. 2022A Relational Intervention Approach for Unsupervised Dynamics Generalization in Model-Based Reinforcement Learningcited by 15
  10. 2021On Covariate Shift of Latent Confounders in Imitation and Reinforcement Learningcited by 14
  11. 2022Survey on Fair Reinforcement Learning: Theory and Practicecited by 14
  12. 2022Causal Entropy Optimizationcited by 13
  13. 2021Bandit Algorithms for Precision Medicinecited by 12
  14. 2023Causal Bandits without Graph Learningcited by 10
  15. 2023Additive Causal Bandits with Unknown Graphcited by 10
  16. 2022Combinatorial Pure Exploration of Causal Banditscited by 9
  17. 2021Operationalizing Complex Causes: A Pragmatic View of Mediationcited by 8
  18. 2021Causal Markov Decision Processes: Learning Good Interventions Efficientlycited by 7
  19. 2023Combinatorial Causal Bandits without Graph Skeletoncited by 7
  20. 2023Intervention Generalization: A View from Factor Graph Modelscited by 7
  21. 2024Causal Bandits with General Causal Models and Interventionscited by 7
  22. 2023Competing for Shareable Arms in Multi-Player Multi-Armed Banditscited by 6
  23. 2023Constrained Causal Bayesian Optimizationcited by 6
  24. 2023Learning Good Interventions in Causal Graphs via Coveringcited by 5
  25. 2023Functional Causal Bayesian Optimizationcited by 5
  26. 2023Exploiting Causal Graph Priors with Posterior Sampling for Reinforcement Learningcited by 5
  27. 2024Causality from Bottom to Top: A Surveycited by 5
  28. 2024Causally Abstracted Multi-armed Banditscited by 5
  29. 2024Adaptive Experimentation When You Can't Experimentcited by 5
  30. 2024Partially Observable Contextual Bandits with Linear Payoffscited by 5
  31. 2024Best Arm Identification with Minimal Regretcited by 5
  32. 2024Linear Causal Bandits: Unknown Graph and Soft Interventionscited by 5
  33. 2024Partial Structure Discovery is Sufficient for No-regret Learning in Causal Banditscited by 5
  34. 2025Graph-Dependent Regret Bounds in Multi-Armed Bandits with Interferencecited by 5
  35. 2022Linear Combinatorial Semi-Bandit with Causally Related Rewardscited by 4
  36. 2023Robust Causal Bandits for Linear Modelscited by 4
  37. 2024Confounded Budgeted Causal Banditscited by 4
  38. 2024Counterfactual Influence in Markov Decision Processescited by 4

50 most cited of 100 All 100 (JSON)