mlsanityData to 14 Oct 2026

Model-based Causal Bayesian Optimization

arXiv 2211.10257 ↗First posted 18 Nov 2022cs.LG stat.MLcited by 26

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Abstract (arXiv)

How should we intervene on an unknown structural equation model to maximize a downstream variable of interest? This setting, also known as causal Bayesian optimization (CBO), has important applications in medicine, ecology, and manufacturing. Standard Bayesian optimization algorithms fail to effectively leverage the underlying causal structure. Existing CBO approaches assume noiseless measurements and do not come with guarantees. We propose the model-based causal Bayesian optimization algorithm (MCBO) that learns a full system model instead of only modeling intervention-reward pairs. MCBO propagates epistemic uncertainty about the causal mechanisms through the graph and trades off exploration and exploitation via the optimism principle. We bound its cumulative regret, and obtain the first non-asymptotic bounds for CBO. Unlike in standard Bayesian optimization, our acquisition function cannot be evaluated in closed form, so we show how the reparameterization trick can be used to apply gradient-based optimizers. The resulting practical implementation of MCBO compares favorably with state-of-the-art approaches empirically.

Key facts. Cited by 26 papers in the map (data through 14 Oct 2026). Builds on 12 of its 24 references that are in the map. First posted on arXiv 18 Nov 2022.

Builds on

12 of 24 references.

References · 12

  1. 2016Causal Bandits: Learning Good Interventions via Causal Inferencecited by 101
  2. 2020Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planningcited by 86
  3. 2017Lower Bounds on Regret for Noisy Gaussian Process Bandit Optimizationcited by 78
  4. 2020Causal Bayesian Optimizationcited by 39
  5. 2019On Online Learning in Kernelized Markov Decision Processescited by 35
  6. 2021Bayesian Optimization of Function Networkscited by 33
  7. 2022Thinking inside the box: A tutorial on grey-box Bayesian optimizationcited by 26
  8. 2022Causal Bandits for Linear Structural Equation Modelscited by 19
  9. 2021Bayesian Optimization for Cascade-type Multi-stage Processescited by 17
  10. 2020Multi-task Causal Learning with Gaussian Processescited by 14
  11. 2022Causal Entropy Optimizationcited by 13
  12. 2021BoGraph: Structured Bayesian Optimization From Logs for Expensive Systems with Many Parameterscited by 6

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 11; 2024: 9; 2025: 5; 2026: 1.

26 papers.

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  1. 2023Optimistic Active Exploration of Dynamical Systemscited by 32
  2. 2023Efficient Exploration in Continuous-time Model-based Reinforcement Learningcited by 22
  3. 2023Intervention Generalization: A View from Factor Graph Modelscited by 7
  4. 2024Causal Bandits with General Causal Models and Interventionscited by 7
  5. 2025SOMBRL: Scalable and Optimistic Model-Based RLcited by 7
  6. 2023Constrained Causal Bayesian Optimizationcited by 6
  7. 2023Functional Causal Bayesian Optimizationcited by 5
  8. 2024Challenges and Considerations in the Evaluation of Bayesian Causal Discoverycited by 5
  9. 2024Linear Causal Bandits: Unknown Graph and Soft Interventionscited by 5
  10. 2025BONSAI: Structure-exploiting robust Bayesian optimization for networked black-box systems under uncertaintycited by 5
  11. 2023CO-BED: Information-Theoretic Contextual Optimization via Bayesian Experimental Designcited by 4
  12. 2023Adversarial Causal Bayesian Optimizationcited by 4
14 more
  1. 2023Robust Causal Bandits for Linear Modelscited by 4
  2. 2024NeoRL: Efficient Exploration for Nonepisodic RLcited by 4
  3. 2024Causal Bayesian Optimization via Exogenous Distribution Learningcited by 3
  4. 2024No-Regret Learning of Nash Equilibrium for Black-Box Games via Gaussian Processescited by 3
  5. 2025Multi-Objective Causal Bayesian Optimizationcited by 3
  6. 2023Contextual Causal Bayesian Optimisationcited by 2
  7. 2024Improved Bound for Robust Causal Bandits with Linear Modelscited by 2
  8. 2024Asymmetric Graph Error Control with Low Complexity in Causal Banditscited by 2
  9. 2023Bayesian Optimization of Expensive Nested Grey-Box Functionscited by 1
  10. 2024Graph Agnostic Causal Bayesian Optimisationcited by 1
  11. 2023Optimal Observation-Intervention Trade-Off in Optimisation Problems with Causal Structurecited by 0
  12. 2025Causal Bayesian Optimization with Unknown Graphscited by 0
  13. 2025Online Identification of IT Systems through Active Causal Learningcited by 0
  14. 2026Joint Parameter and State-Space Bayesian Optimization: Using Process Expertise to Accelerate Manufacturing Optimizationcited by 0