how to find the optimal path to catch a target when the target is moving using q-learning
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hello i would like to find the optimal action of an agent when the target that he wants to catch is moving using q-learning . My problem that i facing is that i just want to find the optimal optimal next action and not the optimal path to a certain location because the target is moving
i have already build an easier scenario where the agent knows the path of the target and he just finds the optimal path for each move of the target and chooses the optimal path with the least steps but that is unrealistic. In reality the agent will only know the next move of the target and tries to get as much closer as he can in each step. The agent must get trained to find the best predicted move for the next action of the target in order to get closer to it . The actions that i use are up,down,left,right.
if you have any idea on how to make this possible , just let me know.
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Answers (3)
Yatharth
on 6 Jul 2022
You can try considering regions where your target currently is and where it isn't as states
Say your target is at [4,5] so you can assign region from
{ [3,4] , [3,5] , [3,6]
[4,4] , [4,5] , [4,6]
[5,4] , [5,5] , [5,6]} as State = 0 and similarly other regions as different state
and you train your agent to reach that particular region/state. Once you are in that region you can take greedy approch to reach the target
Sabiya Hussain
on 29 Aug 2022
Hello there i need help regarding a Q learning program which is an example of markov decision process of a Recycling robot
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