Formation of adjective, noun and verb concepts through affordances

Download
2012
Yürüten, Onur
In this thesis, we study the development of linguistic concepts (corresponding to a subset of nouns, verbs and adjectives) on a humanoid robot. To accomplish this goal, we use affordances, a notion first proposed by J.J. Gibson to describe the action possibilities offered to an agent by the environment. Using the affordances formalization framework of Sahin et al., we have implemented a learning system on a humanoid robot and obtained the required data from the sensorimotor experiences of the robot. The system we developed (1) can learn verb, adjective and noun concepts, (2) represent them in terms of strings of prototypes and dependencies based on affordances, (3) can accurately recognize the concept of novel objects and events, and (4) can be used for tasks such as goal emulation and multi step planning.

Suggestions

Verb concepts from affordances
Kalkan, Sinan; Yuerueten, Onur; Borghi, Anna M.; Şahin, Erol (John Benjamins Publishing Company, 2014-01-01)
In this paper, we investigate how the interactions of a robot with its environment can be used to create concepts that are typically represented by verbs in language. Towards this end, we utilize the notion of affordances to argue that verbs typically refer to the generation of a specific type of effect rather than a specific type of action. Then, we show how a robot can form these concepts through interactions with the environment and how humans can use these concepts to ease their communication with the r...
The learning of adjectives and nouns from affordance and appearance features
Yürüten, Onur; Şahin, Erol; Kalkan, Sinan (SAGE Publications, 2013-8-22)
We study how a robot can link concepts represented by adjectives and nouns in language with its own sensorimotor interactions. Specifically, an iCub humanoid robot interacts with a group of objects using a repertoire of manipulation behaviors. The objects are labeled using a set of adjectives and nouns. The effects induced on the objects are labeled as affordances, and classifiers are learned to predict the affordances from the appearance of an object. We evaluate three different models for learning adjecti...
Integrating Spatial Concepts into a Probabilistic Concept Web
Celikkanat, Hande; Şahin, Erol; Kalkan, Sinan (2015-07-31)
In this paper, we study the learning and representation of grounded spatial concepts in a probabilistic concept web that connects them with other noun, adjective, and verb concepts. Specifically, we focus on the prepositional spatial concepts, such as "on", "below", "left", "right", "in front of" and "behind". In our prior work (Celikkanat et al., 2015), inspired from the distributed highly-connected conceptual representation in human brain, we proposed using Markov Random Field for modeling a concept web o...
Investigation of semantic effects in oddball paradigm through event related potentials
Dumlu, Seda Nilgün; Gökçay, Didem; Öniz, Adile; Department of Medical Informatics (2012)
In this study, the effect of semantic information processing was investigated by the oddball paradigm, by presenting consecutive Turkish words or word-like non-words while EEG signals are recorded. In an oddball paradigm, a series of events are presented of which one class is rarer than the other. Subjects are asked to respond to the infrequent stimuli (e.g. press a button, or count the number). The event related potential (ERP) component P300 obtained from EEG is considered as the marker of this attention ...
Building a web of concepts on a humanoid robot
Orhan, Güner; Kalkan, Sinan; Department of Computer Engineering (2014)
In this thesis, an effective approach for predicting nouns, adjectives and verbs is introduced for more effective communication between a humanoid robot and a human actor. There are three important challenges addressed by our approach: The first one is the accurate prediction of words in language. Most of the existing robotics studies predict words in language using perceptual information only. However, due to noise and ambiguity in low-level sensory information, prediction using perceptual information is o...
Citation Formats
O. Yürüten, “Formation of adjective, noun and verb concepts through affordances,” M.S. - Master of Science, Middle East Technical University, 2012.