In this assignment, students must code and implement one of the reinforcement learning algorithms taught in the class. The algorithm will be used to develop an Agent that could optimally push the box into the end goal without falling into the cliff. All events occur within a 2D cartesian plane. Students could also modify or redesign the algorithms for bonus marks. For my work, I developed a custom Q-Learning algorithm called pQ-Learning which could learn the optimal movement faster than the original q-Learning, with lesser iteration loops relative to the original Q-Learning. This is done by remembering a predefined X historical movement rather than just the last movement and update the weighs of the X historical movement after each move rather than just the last move
Only for the reference of curious people, eager to learn something new.
Please check the plagiarism rules. I do not support any misuse of the source code.
Final Grade: A
The content in this repository should exclusively be utilized in sharing solutions for projects, communicating ideas for related problems, and references to similar assignments. If you are a student facing an assignment with the same or similar topics, you can use this repository as a reference, while the final report should include the citations of the repository. If you submit an assignment without proper acknowledgment after referring to this repository, you may be considered PLAGIARISM by your instructor, and the author will not pay ANY responsibility for this. Please refer to your teacher's and your school's instructions for the determination of academic integrity.
Moreover, if you are taking the AI6101 course, do not be stupid. You can utilize the materials here as a reference to construct your own assignment and reflect the citation to this repository in the final report. If you copy the code without citing it, you have violated NTU's academic integrity and are involved in plagiarism.
Please refer to the following links for NTU's determination of academic integrity and plagiarism
If you think the professor is easy to fool, think again.
This repository should only be used for reasonable academic discussions. I, the owner of this repository, never and will never ALLOWING another student to copy this assignment as their own. In such circumstances, I do not violate NTU's statement on academic integrity as of the time this repository is open (29/08/2023). I am not responsible for any future plagiarism using the content of this repository.
[AI6101] Introduction to AI & AI Ethics is a core course of Master of Science in Artificial Intelligence Graduate Programme (MSAI), School of Computer Science and Engineering (SCSE), Nanyang Technological University (NTU), Singapore. The repository corresponds to the AI6101 of Semester 2, AY2022-2023, starting from 01/2023.
All of above projects are designed by Prof. Bo An. Readme notes designed by AccSrd