Fang Meng, Assistant Professor (PhD supervisor) from the University of Liverpool, UK

发布者:李茜发布时间:2023-11-28浏览次数:10

At 10 am on November 25th, the School of Intelligent Science and Technology invited Assistant Professor Fang Meng (PhD supervisor) from the University of Liverpool, UK, to give an academic report entitled Language Agents and Text Games.


Abstract: In the field of gaming, text games are experiencing a renaissance, providing players with unique and immersive gaming experiences.This discussion focuses on how to integrate natural language processing technology, especially language agents, into text games to make them behave like humans in participating in the game.We have conducted in-depth research on the application of language agents in knowledge expression, reasoning, decision-making, and other aspects, striving to achieve more powerful agents.In addition, we also explore the ethical issues involved in applying language agents in games, with a particular focus on the potential impact related to morality.We discuss strategies to alleviate these challenges and responsibly apply AI in games.Through these discussions, we are committed to promoting the development of language agents in the field of gaming to enhance the language understanding, reasoning, and decision-making abilities of agents.


The presenter: Fang Meng, Assistant Professor (PhD supervisor) at the University of Liverpool, United Kingdom, and Visiting Assistant Professor at Eindhoven University of Technology, Netherlands.His research focuses on enhancing agents and intelligent systems through language, enabling them to understand and interact with humans in the real world, including language understanding, reasoning, and decision-making capabilities.His main research areas include natural language processing and reinforcement learning/machine learning.He has published more than 40 papers in international top-level conferences and journals in NLP and AI. He has won many best papers and nominations in international conferences, and his work has won the Best Paper Award of the Graph Learning Conference LoG-2022.