Q-Learning for Reachability in MEC-Free MDPs

arXiv:2610.01781 · cs.AI, cs.LG, cs.LO · Submitted 2026-10-01 · Read on arXiv

cs.AI, cs.LG, cs.LO

Submitted: 2026-10-01

Updated: 2026-10-01

Comments: 15 pages, 4 figures

Code: https://github.com/amoghp214/asymptotic-ltlreachability

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Q-learning — 1× in this paper · explained in 3 episodes

Sources

• A Survey of Exploration Methods in Reinforcement Learning

Related papers

• MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
• Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models
• Agents' Last Exam
• The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing
• MindHelper: Closed-Loop Embodied Mental-State Reasoning for Precision Intervention
• Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems