Recurrent Neural Networks (RNNs) are effective tools for processing sequential data.

However, it is not directly applicable to Reinforcement Learning (RL) due to the inaccessibility of explicit action-value functions.

Decision trees are a fundamental workhorse in machine learning. Their logical and hierarchical structure makes them easy to understand and their predictions easy to explain.

Multi-task learning is a promising paradigm for handling several tasks simultaneously using a unified architecture.