Emergence of verb and object concepts through learning affordances

Dağ, Nilgün
Researchers are still far from thoroughly understanding and building accurate computational models of the mechanisms in human mind that give rise to cognitive processes such as emergence of concepts and language acquisition. As a new attempt to give an insight into this issue, in this thesis, we are concerned about developing a computational model that leads to the emergence of concepts. Speci cally, we investigate how a robot can acquire verb and object concepts through learning affordances, a notion first proposed by J. J. Gibson in 1986. Using the affordance formalization framework of Şahin et al. in 2007, a humanoid robot acquires concepts through interactions in an embodied environment. For the acquisition of verb concepts, we take an alternative approach to the literature, which generally links verbs to specific behaviors of the robot, by linking them to specific effects that different behaviors may generate. We show how our robot can learn effect prototypes, represented in terms of feature changes in the perception vector of the robot, through demonstrations made by a human supervisor. As for the object concepts, we use the affordance relations of objects to create object concepts based on their functional relevance. Additionally, we show that the extracted e ect prototypes corresponding to verb concepts can also be utilized to discover stable and variable properties of objects which can be associated to stable and variable affordances. Moreover, we show that the acquired concepts provide a suitable basis for communication with humans or other agents, for example to understand and imitate others' behaviors or for goal speci cation tasks. These capabilities are demonstrated in simple interaction games on the iCub humanoid robot platform.


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Citation Formats
N. Dağ, “Emergence of verb and object concepts through learning affordances,” M.S. - Master of Science, Middle East Technical University, 2010.