Research map / Bandits and online learning / Contextual bandits and Thompson sampling
Causal Bandits for Linear Structural Equation Models
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Studies causal bandits for linear structural equation models, aiming to find interventions that maximize a reward variable in a causal graph.
Problem
Identifying optimal interventions in a causal system with unknown linear structural equations, where the goal is to maximize a reward variable through sequential interventions.
Approach
Applies bandit-style sequential decision making over interventions in linear structural equation models, exploiting causal structure to reduce the search space; the abstract does not specify details beyond this.
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