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Probabilistic Evaluation of Sequential Plans from Causal Models with Hidden Variables

arXiv 1302.4977 ↗First posted 20 Feb 2013cs.AIcited by 23

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Abstract (arXiv)

The paper concerns the probabilistic evaluation of plans in the presence of unmeasured variables, each plan consisting of several concurrent or sequential actions. We establish a graphical criterion for recognizing when the effects of a given plan can be predicted from passive observations on measured variables only. When the criterion is satisfied, a closed-form expression is provided for the probability that the plan will achieve a specified goal.

Key facts. Cited by 23 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 Feb 2013.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 4; 2022: 5; 2023: 3; 2024: 2; 2025: 7; 2026: 2.

23 papers.

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  1. 2021Nested Counterfactual Identification from Arbitrary Surrogate Experimentscited by 38
  2. 2022Developing Optimal Causal Cyber-Defence Agents via Cyber Security Simulationcited by 37
  3. 2022Sequential Causal Imitation Learning with Unobserved Confounderscited by 25
  4. 2022Causal Inference Using Tractable Circuitscited by 12
  5. 2023Characterization and Learning of Causal Graphs with Small Conditioning Setscited by 11
  6. 2021Causal Effect Identification with Context-specific Independence Relations of Control Variablescited by 8
  7. 2021Ambiguous Dynamic Treatment Regimes: A Reinforcement Learning Approachcited by 6
  8. 2024Interventional Fairness on Partially Known Causal Graphs: A Constrained Optimization Approachcited by 6
  9. 2025Differentiable Constraint-Based Causal Discoverycited by 4
  10. 2025Kernel-based estimators for functional causal effectscited by 3
  11. 2025Exploring Consciousness in LLMs: A Systematic Survey of Theories, Implementations, and Frontier Riskscited by 3
  12. 2022Tree-based Subgroup Discovery In Electronic Health Records: Heterogeneity of Treatment Effects for DTG-containing Therapiescited by 2
11 more
  1. 2022Causal Modeling of Policy Interventions From Sequences of Treatments and Outcomescited by 2
  2. 2023Bayesian causal discovery from unknown general interventionscited by 2
  3. 2025Density Ratio-Free Doubly Robust Proxy Causal Learningcited by 1
  4. 2025On Transportability for Structural Causal Banditscited by 1
  5. 2026Causal Flow Q-Learning for Robust Offline Reinforcement Learningcited by 1
  6. 2026Computational Identifiabilitycited by 1
  7. 2021Improving Causal Effect Estimation of Weighted RegressionBased Estimator using Neural Networkscited by 0
  8. 2023Optimal Observation-Intervention Trade-Off in Optimisation Problems with Causal Structurecited by 0
  9. 2024Graph Partial Label Learning with Potential Cause Discoveringcited by 0
  10. 2025Practically Effective Adjustment Variable Selection in Causal Inferencecited by 0
  11. 2025Response to Discussions of "Causal and Counterfactual Views of Missing Data Models"cited by 0