Incremental Learning of Affordances using Markov Logic Networks
Incremental Learning of Affordances using Markov Logic Networks
Affordances enable robots to have a semantic understanding of their surroundings. This allows them to have more acting flexibility when completing a given task. Capturing object affordances in a machine learning model is a difficult task, because of their dependence on contextual information. Markov Logic Networks (MLN) combine probabilistic reasoning …