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...
محفوظ في:
المؤلف الرئيسي: | |
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مؤلفون آخرون: | |
التنسيق: | Final Year Project |
اللغة: | English |
منشور في: |
Nanyang Technological University
2024
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الموضوعات: | |
الوصول للمادة أونلاين: | https://hdl.handle.net/10356/175216 |
الوسوم: |
إضافة وسم
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الملخص: | 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’. |
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