Learning Actionable Counterfactual Explanations in Large State Spaces

arXiv:2404.17034v1 Announce Type: new
Abstract: Counterfactual explanations (CFEs) are sets of actions that an agent with a negative classification could take to achieve a (desired) positive classification, for consequential decisions such as loan applications, hiring, admissions, etc. In this work, we consider settings where optimal CFEs correspond to solutions of weighted set cover problems. In particular, there is a collection of actions that agents can perform that each have their own cost and each provide the agent with different sets …

abstract admissions agent applications arxiv classification counterfactual cs.lg decisions etc hiring negative positive set solutions spaces state type work