Markov Decision Processes
A mathematical framework for modeling decision-making in situations where outcomes are partly random and partly under the control of a decision-maker.
Description
Markov Decision Processes (MDPs) provide a mathematical framework for modeling decision making in situations where outcomes are partly random and partly under the control of a decision maker. MDPs are useful for studying optimization problems solved via dynamic programming and reinforcement learning. An MDP is defined by its state and action spaces and the one-step dynamics of the environment.
Examples
- 🤖 Robot navigation
- 📦 Inventory management
- 🃏 Poker playing AI
Applications
Related Terms
Featured
Tidio
Smart, human-like support powered by AI — available 24/7.
Animon AI
Create anime videos for free
ChatGPT Atlas
The browser with ChatGPT built in
Wan AI
Generate cinematic videos from text, image, and speech
Higgsfield AI
Cinematic AI video generator with pro VFX control
Neurona AI Image Creator
AI image generator; AI art generator; face swap AI
AI Text Summarizer
AI Text Summarizer That Rocks: Faster Content Analysis
Kimi AI
Kimi AI - K2 chatbot for long-context coding and research
Free AI PDF Reader
Free AI PDF Reader – Smarter Way to Understand Any PDF
Free AI Article Summarizer
Free Article Summarizer
Google Nano Banana
Fast multimodal Gemini model for production
AI Book Summarizer
AI Book Summarizer That Makes Books Easy to Grasp
Blackbox AI
Accelerate development with Blackbox AI's multi-model platform
Ask AI Questions Online
Ask AI Questions for Free – Smart, Fast, and Human-Like Answers
Sora 2
Transform Ideas into Stunning Videos with Sora 2
Abacus AI
The World's First Super Assistant for Professionals and Enterprises
