Chapter 100: The Future of Reinforcement Learning
Learning objectives Write a short essay (1–2 pages) on how foundation models (large pretrained models for language, vision, or multimodal) might impact reinforcement learning. Discuss potential architectures for decision-making that leverage large-scale pretraining (e.g. RL fine-tuning of LMs, world models with foundation model representations, or agents that use foundation models as policies or critics). Speculate on the path toward AGI (or toward more general and capable agents) from the perspective of RL + foundation models: what is missing, what might scale, and what risks or open problems remain. Use concepts from the curriculum (value functions, policy gradients, offline RL, multi-agent, safety, RLHF) where relevant. Relate to anchor scenarios (robot navigation, game AI, recommendation, trading, healthcare, dialogue) and where foundation models are already or could be applied. Concept and real-world RL ...