Reinforcement Learning for Generative AI: State of the Art, Opportunities and Open Research Challenges

Abstract

Generative Artificial Intelligence (AI) is one of the most exciting developments in Computer Science of the last decade. At the same time, Reinforcement Learning (RL) has emerged as a very successful paradigm for a variety of machine learning tasks. In this survey, we discuss the state of the art, opportunities and open research questions in applying RL to generative AI. In particular, we will discuss three types of applications, namely, RL as an alternative way for generation without specified objectives; as a way for generating outputs while concurrently maximizing an objective function; and, finally, as a way of embedding desired characteristics, which cannot be easily captured by means of an objective function, into the generative process. We conclude the survey with an in-depth discussion of the opportunities and challenges in this fascinating emerging area.

How Can the Current State of AI Guide Future Conversations of General Intelligence?

“…The debates cover various aspects of intelligence. For example, Franceschelli and Musolesi ( 2023 ) argue that LLMs can create content that meets the highly cited creativity criteria developed by Boden ( 1991 ), which require that created products are “new, surprising and valuable.” They admit, however, to only observe weak forms of creativity as opposed to transformational creativity, likely due to a lack of processes such as motivation. Andreas ( 2022 ) argues that LLMs possess intentions but in the narrow sense as modules within communicative agents.…”

An Investigation into the Utility of Large Language Models in Geotechnical Education and Problem Solving

“…This shift is prominently marked by the emergence of Generative AI as a pivotal force in reshaping educational paradigms, offering innovative approaches to learning and problemsolving [5][6][7]. Central to this AI-driven revolution in education are generative AI models such as large language models (LLMs) like ChatGPT [8][9][10][11][12][13], which have demonstrated considerable potential in enhancing learning outcomes [14][15][16] and aiding in complex problem-solving scenarios. These models, powered by sophisticated algorithms and extensive data, can alter information delivery and fundamentally change how students interact with and comprehend complex topics [17].…”