Reinforcement Learning
Ethics Content Description
The ethics component addresses the problem of value alignment and gets students to consider the implications of different targets of alignment (e.g., user intentions, user preferences, users' best interests, moral right and wrong) in the context of LLM chatbots. Students are also introduced to the basics of some moral theories and consider the question of whether these theories offer us any help in creating value-aligned AI.
Course Description
To realize the dreams and impact of AI requires autonomous systems that learn to make good decisions. Reinforcement learning is one powerful paradigm for doing so, and it is relevant to an enormous range of tasks, including robotics, game playing, consumer modeling and healthcare. This class will briefly cover background on Markov decision processes and reinforcement learning, before focusing on some of the central problems, including scaling up to large domains and the exploration challenge. One key tool for tackling complex RL domains is deep learning and this class will include at least one homework on deep reinforcement learning.
Contributors
Ethics materials created by Daniel Webber.