AI based serious game design - Kleptomancy

In this paper, we explored the use of Artificial Intelligence to create an adversary that demonstrates reasonable intelligence through the extensive use of Machine Learning techniques, Deep Reinforcement Learning and Imitation Learning techniques. In particular, we used Proximal Policy Optimizati...

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Main Author: Wee, Chang Han
Other Authors: Smitha Kavallur Pisharath Gopi
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2024
Subjects:
Online Access:https://hdl.handle.net/10356/175216
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1752162024-04-26T15:41:41Z AI based serious game design - Kleptomancy Wee, Chang Han Smitha Kavallur Pisharath Gopi School of Computer Science and Engineering smitha@ntu.edu.sg Computer and Information Science Engineering Artificial intelligence Reinforcement learning Machine learning Generative adversarial imitation learning Self-play Serious game In this paper, we explored the use of Artificial Intelligence to create an adversary that demonstrates reasonable intelligence through the extensive use of Machine Learning techniques, Deep Reinforcement Learning and Imitation Learning techniques. In particular, we used Proximal Policy Optimization (PPO) algorithm, a branch of Model-Free RL Policy Optimization model, as well as Generative Adversarial Imitation Learning (GAIL) to train our intelligent agent. This project aims to evaluate and demonstrate the Intelligent Agent’s adaptive responses and strategies when faced with player-generated challenges in an edutainment game that was developed as part of this project, ‘Kleptomancy’. Bachelor's degree 2024-04-21T12:06:46Z 2024-04-21T12:06:46Z 2024 Final Year Project (FYP) Wee, C. H. (2024). AI based serious game design - Kleptomancy. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/175216 https://hdl.handle.net/10356/175216 en SCSE23-0471 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Computer and Information Science
Engineering
Artificial intelligence
Reinforcement learning
Machine learning
Generative adversarial imitation learning
Self-play
Serious game
spellingShingle Computer and Information Science
Engineering
Artificial intelligence
Reinforcement learning
Machine learning
Generative adversarial imitation learning
Self-play
Serious game
Wee, Chang Han
AI based serious game design - Kleptomancy
description In this paper, we explored the use of Artificial Intelligence to create an adversary that demonstrates reasonable intelligence through the extensive use of Machine Learning techniques, Deep Reinforcement Learning and Imitation Learning techniques. In particular, we used Proximal Policy Optimization (PPO) algorithm, a branch of Model-Free RL Policy Optimization model, as well as Generative Adversarial Imitation Learning (GAIL) to train our intelligent agent. This project aims to evaluate and demonstrate the Intelligent Agent’s adaptive responses and strategies when faced with player-generated challenges in an edutainment game that was developed as part of this project, ‘Kleptomancy’.
author2 Smitha Kavallur Pisharath Gopi
author_facet Smitha Kavallur Pisharath Gopi
Wee, Chang Han
format Final Year Project
author Wee, Chang Han
author_sort Wee, Chang Han
title AI based serious game design - Kleptomancy
title_short AI based serious game design - Kleptomancy
title_full AI based serious game design - Kleptomancy
title_fullStr AI based serious game design - Kleptomancy
title_full_unstemmed AI based serious game design - Kleptomancy
title_sort ai based serious game design - kleptomancy
publisher Nanyang Technological University
publishDate 2024
url https://hdl.handle.net/10356/175216
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