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Printer.pdf

po-f01-handout4.pdf

🔗 Source: ai.dmi.unibas.ch

📊 Size: 2.57 MB

👤 Author: Malte Helmert and Thomas Keller

⬇️ Downloads: 112

Summary

Markov Decision Processes (MDPs) are a generalization of classical planning, used for temporal planning, numeric planning, and probabilistic planning. MDPs are a fundamental data structure for reinforcement learning and probabilistic planning. A Markov decision process is a 6-tuple consisting of a finite set of states, a finite set of actions, a reward function, a transition function, an initial state, and a discount factor. The transition function specifies the probability of transitioning from one state to another when taking a particular action. The goal is to find a policy that maximizes the expected cumulative reward. MDPs are closely related to games and are used in various applications, including logistics, robotics, and finance.

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Description

Markov Decision Processes (MDPs) are a generalization of classical planning, used for temporal planning, numeric planning, and probabilistic planning.

Technical Information

File Format: PDF
File Size: 2.57 MB
Pages: 8
Language: EN
Author: Malte Helmert and Thomas Keller
Total Downloads: 112
Last Updated: 6 hours ago

Document Overview

This PDF document about printer provides comprehensive information and guidance. Whether you're a beginner or advanced user, this resource offers valuable insights into printer.