Summary of neural network architecture.

<div><p>Reinforcement learning is a remarkable aspect of the artificial intelligence field with many applications. Reinforcement learning facilitates learning new tasks based on action and reward principles. Motion planning addresses the navigation problem for robots. Current motion plan...

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Bibliographic Details
Main Author:	Raed Alharthi (18340157) (author)
Other Authors:	Iram Noreen (12334120) (author), Amna Khan (735548) (author), Turki Aljrees (16715369) (author), Zoraiz Riaz (20571028) (author), Nisreen Innab (20389920) (author)
Published:	2025
Subjects:	Sociology Science Policy Mental Health Space Science Biological Sciences not elsewhere classified Information Systems not elsewhere classified robotic systems due could help deal artificial intelligence field art comparison shows motion planning addresses based motion planning problem becomes worse based reinforcement algorithm reward system ’ task learning due deep learning integration th </ sup proposed approach ’ div >< p cluttered passage environment causes late convergence complex environment cluttered narrow passage environment proposed approach cluttered environment complex environment reinforcement learning navigation problem reward principles reward policies path planning timely responses research presents remarkable aspect processing requirements novel q many applications less responsive less efficient issues using existing algorithms computationally expensive collision avoidance agent converged
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Summary of neural network architecture.

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