David Abel on the Science of Agency @ RLDM 2025
TalkRL: The Reinforcement Learning Podcast
00:00
Redefining Continual Reinforcement Learning
This chapter explores a novel perspective on continual reinforcement learning, emphasizing the adaptive nature of agents in dynamic environments. It contrasts traditional paradigms of fixed solutions with lifelong learning, highlighting the importance of agents' ability to navigate shifting Markov Decision Processes (MDPs). Through the analogy of sages examining an elephant, the discussion underscores the complexity of agency and its evolution, proposing a frame-dependent understanding of learning and adaptation in AI.
Transcript
Play full episode
