Bridging Impulse Control of Piecewise Deterministic Markov Processes and Markov Decision Processes: Frameworks, Extensions, and Open Challenges

arXiv:2501.04120 · stat.ME, cs.SY, eess.SY · Submitted 2025-01-07 · Read on arXiv

stat.ME, cs.SY, eess.SY

Submitted: 2025-01-07

Updated: 2026-09-24

Terminology

• Action Space — 25× in this paper · explained in 1 episode
• Reinforcement Learning — 24× in this paper · explained in 4 episodes
• Q-learning — 14× in this paper · explained in 3 episodes
• Markov Decision Process — 13× in this paper
• Deep Reinforcement Learning — 6× in this paper · explained in 2 episodes
• Piecewise Deterministic Markov Process — 5× in this paper
• Deep Q-Network — 4× in this paper
• Markov Decision Process (MDP) — 4× in this paper · explained in 11 episodes
• Monte Carlo Tree Search — 4× in this paper
• Adaptation — 3× in this paper · explained in 1 episode
• Bayesian Framework — 3× in this paper · explained in 3 episodes
• Bayesian Reinforcement Learning — 3× in this paper
• Abstraction — 2× in this paper · explained in 1 episode
• Diffusion Processes — 2× in this paper · explained in 2 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• In International Conference on Machine Learning — 2× in this paper
• Partially Observable Markov Decision Process — 2× in this paper
• Predictive Maintenance — 2× in this paper · explained in 2 episodes
• Quantization — 2× in this paper · explained in 12 episodes
• Reinforcement Learning (RL) — 2× in this paper · explained in 25 episodes
• Stochastic Dynamics — 2× in this paper · explained in 2 episodes
• Stochastic Simulation Algorithm — 2× in this paper
• Accuracy — 1× in this paper · explained in 1 episode
• Bayesian Adaptive Monte Carlo Planning — 1× in this paper
• Bayesian Inference — 1× in this paper · explained in 5 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Curse of Dimensionality — 1× in this paper · explained in 6 episodes
• Hybrid System — 1× in this paper · explained in 2 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Ordinary Differential Equations (ODEs) — 1× in this paper · explained in 2 episodes
• Pruning — 1× in this paper · explained in 4 episodes
• Reward Function — 1× in this paper · explained in 2 episodes
• Theoretical Guarantees — 1× in this paper · explained in 2 episodes
• World Model — 1× in this paper · explained in 7 episodes

Sources

• OpenAI Gym
• Mastering Diverse Domains through World Models
• Playing Atari with Deep Reinforcement Learning
• Proximal Policy Optimization Algorithms
• A new twist for the simulation of hybrid systems using the true jump method
• Dueling Network Architectures for Deep Reinforcement Learning

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