mlsanityData to 14 Oct 2026

Dynamic Causal Bayesian Optimization

arXiv 2110.13891 ↗First posted 26 Oct 2021stat.ML cs.LGcited by 17

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Abstract (arXiv)

This paper studies the problem of performing a sequence of optimal interventions in a causal dynamical system where both the target variable of interest and the inputs evolve over time. This problem arises in a variety of domains e.g. system biology and operational research. Dynamic Causal Bayesian Optimization (DCBO) brings together ideas from sequential decision making, causal inference and Gaussian process (GP) emulation. DCBO is useful in scenarios where all causal effects in a graph are changing over time. At every time step DCBO identifies a local optimal intervention by integrating both observational and past interventional data collected from the system. We give theoretical results detailing how one can transfer interventional information across time steps and define a dynamic causal GP model which can be used to quantify uncertainty and find optimal interventions in practice. We demonstrate how DCBO identifies optimal interventions faster than competing approaches in multiple settings and applications.

Key facts. Cited by 17 papers in the map (data through 14 Oct 2026). Builds on 19 of its 58 references that are in the map. First posted on arXiv 26 Oct 2021.

Builds on

19 of 58 references.

References · 19

  1. 2017Counterfactual Multi-Agent Policy Gradientscited by 751
  2. 2019Explainable Reinforcement Learning Through a Causal Lenscited by 177
  3. 2015Multi-armed Bandit Models for the Optimal Design of Clinical Trials: Benefits and Challengescited by 114
  4. 2016Causal Bandits: Learning Good Interventions via Causal Inferencecited by 101
  5. 2018Woulda, Coulda, Shoulda: Counterfactually-Guided Policy Searchcited by 82
  6. 2016Time-Varying Gaussian Process Bandit Optimizationcited by 50
  7. 2019Causal Discovery and Forecasting in Nonstationary Environments with State-Space Modelscited by 45
  8. 2014From Ordinary Differential Equations to Structural Causal Models: the deterministic casecited by 41
  9. 2020Causal Bayesian Optimizationcited by 39
  10. 2018Deconfounding Reinforcement Learning in Observational Settingscited by 36
  11. 2020Causal models for dynamical systemscited by 34
  12. 2016From Deterministic ODEs to Dynamic Structural Causal Modelscited by 32
7 more
  1. 2013Directed Cyclic Graphical Representations of Feedback Modelscited by 28
  2. 2018Learning Contextual Bandits in a Non-stationary Environmentcited by 26
  3. 2020Multi-task Causal Learning with Gaussian Processescited by 14
  4. 2018Bayesian Optimization for Dynamic Problemscited by 10
  5. 2013Identifying Independencies in Causal Graphs with Feedbackcited by 7
  6. 2020Causal Inference using Gaussian Processes with Structured Latent Confounderscited by 7
  7. 2014Gaussian Process Structural Equation Models with Latent Variablescited by 3

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 1; 2022: 2; 2023: 7; 2024: 2; 2025: 4; 2026: 1.

17 papers.

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  1. 2022Developing Optimal Causal Cyber-Defence Agents via Cyber Security Simulationcited by 37
  2. 2023Causal Deep Learningcited by 20
  3. 2023Inroads into Autonomous Network Defence using Explained Reinforcement Learningcited by 17
  4. 2022Causal Entropy Optimizationcited by 13
  5. 2023Finding Counterfactually Optimal Action Sequences in Continuous State Spacescited by 13
  6. 2024Generative Adversarial Model-Based Optimization via Source Critic Regularizationcited by 10
  7. 2023Functional Causal Bayesian Optimizationcited by 5
  8. 2023Adversarial Causal Bayesian Optimizationcited by 4
  9. 2024Causal Bayesian Optimization via Exogenous Distribution Learningcited by 3
  10. 2025Multi-Objective Causal Bayesian Optimizationcited by 3
  11. 2023Bayesian Optimization of Expensive Nested Grey-Box Functionscited by 1
  12. 2025Causal Discovery via Bayesian Optimizationcited by 1
5 more
  1. 2021Chronological Causal Banditscited by 0
  2. 2023Optimal Observation-Intervention Trade-Off in Optimisation Problems with Causal Structurecited by 0
  3. 2025Causal Bayesian Optimization with Unknown Graphscited by 0
  4. 2025Online Identification of IT Systems through Active Causal Learningcited by 0
  5. 2026Neural Nonmyopic Bayesian Optimization in Dynamic Cost Settingscited by 0