When to Commit and When to Defer: Maturing Markov Decision Processes under Refining Information and Expiring Opportunities
cs.LG, cs.AI
Submitted: 2026-06-17
Updated: 2026-09-27
Comments: 37 pages, 5 figures. Substantially revised formulation, theoretical analysis, and experiments; expanded appendices. Research code: https://github.com/scujx/mmdp (v1.0.0)
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- DeepStock: Reinforcement Learning with Policy Regularizations for Inventory Management
- Maximum Weight Online Matching with Deadlines
- Learning to Cover: Online Learning and Optimization with Irreversible Decisions
- Deep Reinforcement Learning in Parameterized Action Space
- Proximal Policy Optimization Algorithms
- Recurrent Model-Free RL Can Be a Strong Baseline for Many POMDPs
- DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
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