LLM interactions with RL models
RL algorithms have been instrumental for agents that can navigate complex environments, optimize strategies, and make decisions, with successes in areas such as robotics and video games. LLMs, on the other hand, have had a strong impact on natural language processing (NLP), enabling machines to understand human language and instructions. Although potential synergies can be imagined, so far these two technologies have evolved in parallel. In recent years, though, with the heightened interest in LLMs, the two fields have increasingly intersected. In this section, we will discuss the interaction between RL and LLMs.
We can have three cases of interaction:
- RL enhancing an LLM: Using RL to enhance the performance of an LLM in one or more NLP tasks
- LLMs enhancing RL: Using LLMs to train an RL algorithm that performs a task that is not necessarily NLP
- RL and LLMs: Combining RL models and LLMs to plan a skill set, without either system being...
