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Next Best Action: Causal Constrained Offline RL for Business Action Targeting

Paper recorded by Signals 4 on 2026-10-19 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-19 on arXiv · recorded by Signals 4 on 2026-10-20

Category: cs.AI · 人工智能 · first seen 2026-10-20

Abstract

Next Best Action (NBA) systems must select among customer interventions (e.g., discounts, promotions, and lifecycle actions), maximize long-term economic value, satisfy complex operational constraints, and remain causally grounded. Existing approaches lack a rigorous framework for meeting these requirements jointly. We address this gap by formulating NBA as a Constrained Markov Decision Process (C

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#255 most recent of 960 cs.AI papers we have recorded · ↑ newer: AfriBED: a Speech Recognition Bias Evaluation Dataset for Low Resource · ↓ older: Mise-en-Video: Fine-Grained 3D Control for Multi-Shot Video Generation
Cite this page: Next Best Action: Causal Constrained Offline RL for Business Action Targeting: the #255 most recent of 960 cs.AI papers we have recorded (as of 2026-10-19). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/next-best-action-causal-constrained-offline-rl-for-business-action-targeting.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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