Ladies and gentlemen, in a few hours a brilliant PhD student, Giovanni Briglia, will be presenting a paper at an international conference for his very first time!
He will be presenting a paper co-authored by myself, Marco Lippi, and Franco Zambonelli about improving Reinforcement Learning with Causal Reasoning!
The warmest congratulations to Giovanni, bravo!
In brief, the paper proposes an architecture and method to augment an RL algorithm with a causal discovery and inference module: the former enables the agent to learn the cause-effect relationships between state variables of the environment, its own actions, and the expected reward, whereas the latter enables exploiting such knowledge to perform prediction of action effects and planning of actions to reach states.
The key results achieved are:
- the RL algorithms augmented with this causal machinery are more efficient during exploration
- they also converge to more efficient policies
- the learnt causal model enables better generalisation to unseen environments
Here is the published paper: “Improving Reinforcement Learning-Based Autonomous Agents with Causal Models” Feel free to contact me for a pre-print or any further inquiry :)
Peace.
