…relational symbol grounding through affordance learning.
The problem of symbol grounding attempts to associate symbols from language with a corresponding referent in the environment. Traditionally, research has focused on identifying single objects and their properties. Similarly, affordances learning in robotics tend to focus on single objects. These approaches often do not consider the full context of the environment, which contains multiple different objects and their properties as well as relationships among the objects. Furthermore, the state of the environment (e.g., which relationships are true, etc.) affords (i.e., permits executing) certain actions. This project hypothesizes that the grounding process must consider the full context of the environment in order to perform symbol grounding and to better adapt to a new language and a new environment.
Project web page: http://reground.cs.kuleuven.be/