A Grounded and contextualized web of concepts on a humanoid robot

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2015
Çelikkanat, Hande
In this thesis, we propose a formalization for a densely connected representation of concepts and their contexts on a humanoid robot platform. Although concepts have been studied implicitly and explicitly in numerous studies before,our study is unique in placing the relatedness of concepts to the center: We hypothesize that a concept is fully meaningful only when considered in relation to the other concepts. Thus, we propose a novel densely connected web of concepts, and show how utilizing the relatedness of concepts can take cognition one step forward from the conventional approach that treats them individually. Then we use this densely connected framework for determining the context of encountered scenes. Although unanimously accepted as one of the pillars of cognition, our study is the first attempt to provide a dedicated and general formalization of context in a robotics setting. We follow a developmental approach in which the robot determines the existing contexts in its environment in an unsupervised manner, associates seen objects and whole scenes with these contexts as appropriate, and further utilizes this extracted contextual information in reasoning and planning. As required by the developmental paradigm, the programmer’s input to the robot in terms of informational bias is kept at a minimum, and the robot is expected to deduce the important characteristics of the environment itself, such as the number of contexts hidden in its environment, if and when to introduce another context to its world model, and how these contexts probabilistically give rise to the related concepts in this world.

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Citation Formats
H. Çelikkanat, “A Grounded and contextualized web of concepts on a humanoid robot,” Ph.D. - Doctoral Program, Middle East Technical University, 2015.