Reinforcement Learning
In Reinforcement Learning (RL), an agent is guided by the rewards it receives from the reward function. Unfortunately, it may take many …
This paper examines the problem of how to teach multiple tasks to a Reinforcement Learning (RL) agent. To this end, we use Linear …
In this paper we propose Reward Machines – a type of finite state machine that supports the spec- ification of reward functions while …
Convergence to an optimal policy using model-based rein- forcement learning can require significant exploration of the environment. In …
In order to be deployed safely, Large Language Models (LLMs) must be capable of dynamically adapting their behavior based on their …