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Combining Reinforcement Learning and Causal Models for Robotics Applications

Arquímides Méndez-Molina

Year
2021
Citations
6
Access
Open access

Abstract

The relation between Reinforcement learning (RL) and Causal Modeling(CM) is an underexplored area with untapped potential for any learning task. In this extended abstract of our Ph.D. research proposal, we present a way to combine both areas to improve their respective learning processes, especially in the context of our application area (service robotics). The preliminary results obtained so far are a good starting point for thinking about the success of our research project.

Keywords

Reinforcement learningRoboticsArtificial intelligenceComputer scienceContext (archaeology)Task (project management)Point (geometry)Robot learningRelation (database)Machine learning

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