Survey of Deep Neural Networks Handling Plan Development using Simulations of Real-World Environments
Survey of Deep Neural Networks Handling Plan Development using Simulations of Real-World Environments
No Thumbnail Available
Date
2019-12-03
Authors
Askren, Kaleb
Journal Title
Journal ISSN
Volume Title
Publisher
University Honors College Middle Tennessee State University
Abstract
Neural networks are computational models that demonstrate the capability of
advanced computing applications in plan development tasks. Five influential projects
that independently demonstrate various applications of neural network models include
AlphaGO/AlphaGO Zero, Playing Atari with Deep Reinforcement Learning,
NeuroChess, OpenAI Five, and Playing Checkers without Human Expertise. Each of
these projects includes different approaches to plan development tasks and are surveyed
in this thesis using four criteria: the efficiency of the system, the form of their input based
on their target environment, the structure of the neural network(s), and the processes
through which they are trained. Each project approaches the plan development problem
with strict regard to the environment in which they are targeting and thus vary in
implementation. This survey is a collection of the details regarding each project and how
the research teams approached their development
Description
Keywords
Basic and Applied Science,
Neural networks,
AI,
machine learning,
strategy games