Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/175205
Title: Deep reinforcement learning for complex environment 1
Authors: Goh, Peng Aik
Keywords: Computer and Information Science
Issue Date: 2024
Publisher: Nanyang Technological University
Source: Goh, P. A. (2024). Deep reinforcement learning for complex environment 1. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/175205
Project: SCSE23-0059 
Abstract: This project delves into creating an Artificial Intelligence (AI) model tailored for the game Werewolf, focusing on strategic gameplay and realistic interaction. It aims to craft an AI by understanding and adapting to the intricate dynamics of the game and the nuances of player behaviour using deep reinforcement learning and large language models (LLMs). Through this, the project also aims to find out weaknesses in logic of LLMs and how these weaknesses can be alleviated with the aid of reinforcement learning and other means.
URI: https://hdl.handle.net/10356/175205
Schools: School of Computer Science and Engineering 
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

Files in This Item:
File Description SizeFormat 
Goh Peng Aik FYP final report.pdf
  Restricted Access
424.81 kBAdobe PDFView/Open

Page view(s)

155
Updated on May 7, 2025

Download(s)

15
Updated on May 7, 2025

Google ScholarTM

Check

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.