A Perceptual System for Language Game Experiments

Spranger, Michael; Loetzsch, Martin; Steels, Luc

doi:10.1007/978-1-4614-3064-3_5

Cited by 26 publications

(17 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We developed an object vision system that is able to individuate, and track objects in the environment based on earlier work described in [22]. The system works in a series of stages trying to extract foreground-background distinctions, probabilistic object identification and tracking.…”

Section: A Perception Body Models and Basic Behaviorsmentioning

confidence: 99%

Discovering communication through ontogenetic ritualisation

Spranger

Steels

2014

4th International Conference on Development and Learning and on Epigenetic Robotics

Self Cite

View full text Add to dashboard Cite

The entry into symbolic communication through language, gesture or visual signs is one of the key moments in the mental and social development of infants. It is the point from which they start to have a much better social interaction with their parents, other children and adults, and can begin to observe the massive achievements of cultural accumulation. The question addressed in this paper is how developing robots could autonomously make this important transition in their mental development. Based on observations of the way human infants bootstrap into symbolic communication, we propose that gestural symbolic communication comes before auditory symbolic communication and is discovered through a process of ontogenetic ritualisation. The paper identifies the nature of ontogenetic ritualisation and reports on first experiments to achieve this form of learning in humanoid robots.

show abstract

Section: A Perception Body Models and Basic Behaviorsmentioning

confidence: 99%

Discovering communication through ontogenetic ritualisation

Spranger

Steels

2014

4th International Conference on Development and Learning and on Epigenetic Robotics

Self Cite

View full text Add to dashboard Cite

show abstract

“…Both agents perceive the environment using their own camera. The vision system (Spranger et al, 2012a, this volume) computes a situation model (see Figure 9.1, left and right) which is comprised of blocks (circles), boxes (rectangle) and other robots (arrows). The perceiving robot is always the center of the coordinate system which is used to estimate distance and orientation of objects.…”

Section: Spatial Language Gamesmentioning

confidence: 99%

“…Estimation errors Another source of errors and noise is related to algorithms used in object recognition and object feature extraction. For instance, the algorithm for the distance estimation of objects (see Spranger et al, 2012a) has distance estimation error properties shown in Figure 9.3. To estimate the position of objects the algorithm combines noisy sensor readings and integrates them over time and across different sources of information.…”

Section: Sources Of Perceptual Deviationmentioning

confidence: 99%

“…Figure 9.6 shows that for the easy subsets condition both the strict and the lenient approach perform well and reach success in all interactions, the reason is that the information from the vision system (see Spranger et al, 2012a, this volume) for object classes is error and noise free. We can conclude that generalized quantifiers work well, when the knowledge about the state of the world is absolutely accurate and precise.…”

Section: Comparing Clustering To Strict Quantificationmentioning

confidence: 99%

See 1 more Smart Citation

Dealing with Perceptual Deviation: Vague Semantics for Spatial Language and Quantification

Spranger

Pauw

2012

Language Grounding in Robots

Self Cite

View full text Add to dashboard Cite

Grounding language in sensorimotor spaces is an important and difficult task. In order, for robots to be able to interpret and produce utterances about the real world, they have to link symbolic information to continuous perceptual spaces. This requires dealing with inherent vagueness, noise and differences in perspective in the perception of the real world. This paper presents two case studies for spatial language and quantification that show how cognitive operations -the building blocks of grounded procedural semantics -can be efficiently grounded in sensorimotor spaces.

show abstract

“…The referent is either all robots, all blocks or all boxes and agents will always use the determiner "all" in utterances. Figure 9.6 shows that for the easy subsets condition both the strict and the lenient approach perform well and reach success in all interactions, the reason is that the information from the vision system (see Spranger et al, 2012a, this volume) for object classes is error and noise free. We can conclude that generalized quantifiers work well, when the knowledge about the state of the world is absolutely accurate and precise.…”

Section: Comparing Clustering To Strict Quantificationmentioning

confidence: 99%

Language Grounding in Robots

Steels

Hild

2012

View full text Add to dashboard Cite

except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are to proprietary rights.

show abstract

A Perceptual System for Language Game Experiments

Cited by 26 publications

References 40 publications

Discovering communication through ontogenetic ritualisation

Discovering communication through ontogenetic ritualisation

Dealing with Perceptual Deviation: Vague Semantics for Spatial Language and Quantification

Language Grounding in Robots

Contact Info

Product

Resources

About