Partially observable Markov decision process
A partially observable Markov decision process (POMDP) is when we have something we're trying to figure out, but we don't know everything about it. Imagine you're playing hide and seek with your friend, but your friend is hiding in a different room and you can't see where they are. You have to use clues, like hearing them giggle or seeing their shadow, to guess where they might be.
POMDPs work kind of like that. We have a model of something, like a game, but we can't see everything that's happening. We have to use clues, like previous moves or information we're given, to make the best decision we can.
Think of it like a game where you get to choose what you do next, but you don't know everything that's going on. For example, let's say you're playing a game where you have to get to the other side of a maze. You know where the start is, where the end is, and how to move around. But there might be obstacles, like walls or traps, that you can't see. You also don't know for sure what will happen when you take certain actions, like turning left or right.
In this game, a POMDP would help you make decisions based on what you do know. You might try moving in different directions and listening for sounds that indicate you're getting closer to the end. Or you might use a tool, like a map or compass, to help you navigate the maze. You have to use all the information you have to figure out the best move to make.
So that's POMDPs - they're a way to make decisions based on limited information. It's like trying to solve a puzzle without all the pieces. But with the right clues and strategies, you can still make progress and achieve your goals.
POMDPs work kind of like that. We have a model of something, like a game, but we can't see everything that's happening. We have to use clues, like previous moves or information we're given, to make the best decision we can.
Think of it like a game where you get to choose what you do next, but you don't know everything that's going on. For example, let's say you're playing a game where you have to get to the other side of a maze. You know where the start is, where the end is, and how to move around. But there might be obstacles, like walls or traps, that you can't see. You also don't know for sure what will happen when you take certain actions, like turning left or right.
In this game, a POMDP would help you make decisions based on what you do know. You might try moving in different directions and listening for sounds that indicate you're getting closer to the end. Or you might use a tool, like a map or compass, to help you navigate the maze. You have to use all the information you have to figure out the best move to make.
So that's POMDPs - they're a way to make decisions based on limited information. It's like trying to solve a puzzle without all the pieces. But with the right clues and strategies, you can still make progress and achieve your goals.