Evolution of combinatorial structure in learned forms through embodied iterated learning in a robot collective

2020 ◽  
pp. 105971232096857
Author(s):  
Mehmet Dincer Erbas
Keyword(s):  
Social Learning ◽  
Mobile Robots ◽  
High Accuracy ◽  
Combinatorial Structure ◽  
Abstract Model ◽  
Embodied Learning ◽  
Movement Sequences ◽  
Learning Cycles ◽  
Iterated Learning ◽  
Perceptual Abilities

In this study, we use mobile robots as physical entities to model the iterated learning of collections of forms that consist of randomly generated movement sequences. The robots implement an abstract model of embodied iterated social learning in which the forms evolve due to limited perceptual abilities of the robots during multiple learning cycles. It is shown that shared chunks that consisted of similar movement sequences emerge in the learned forms, and as these emergent shared sequences can be learned with high accuracy, they cause a cumulative increase in the learnability of the collections. Therefore, we are able to present robotic experiments in which embodied learning on robots leads to combinatorial structure as a result of cultural interactions in the form of iterated learning without a communicative task.

scholarly journals The emergence of duality of patterning through iterated learning: Precursors to phonology in a visual lexicon

2012 ◽  
Vol 4 (4) ◽  
pp. 381-418 ◽  
Author(s):  
Alex Del Giudice
Keyword(s):  
Design Feature ◽  
Combinatorial Structure ◽  
Human Language ◽  
Lexical Structure ◽  
Small Stock ◽  
Iterated Learning ◽  
Human Participants ◽  
Duality Of Patterning ◽  
Future Work ◽  
Infinite Set

AbstractDuality of Patterning, one of Hockett's (1960) proposed design features unique to human language, refers in part to the arrangements of a relatively small stock of distinguishable meaningless sounds which are combined to create a potentially infinite set of morphemes. Literature regarding the emergence of this design feature is less abundant than that exploring other levels of structure as focus is more often given to the emergence of syntax. In an effort to explore where combinatorial structure of meaningless elements arises the results of two pilot experiments are presented within which we observe human participants modifying a small lexicon of visual symbols through a process of iterated learning. As this lexicon evolves there is evidence that it becomes simpler and more learnable, more easily transmitted. I argue that these features are a consequence of spontaneous emergence of combinatorial, sub-lexical structure in the lexicon, that the pattern of emergence is more complex than the most widely espoused explanation suggests, and I propose ways in which future work can build on what we learn from these pilot experiments to confirm this hypothesis.

LANGUAGE DYNAMICS IN STRUCTURED FORM AND MEANING SPACES

2012 ◽  
Vol 15 (03n04) ◽  
pp. 1150021 ◽  
Author(s):  
BART DE BOER ◽  
TESSA VERHOEF
Keyword(s):  
Complex Form ◽  
Combinatorial Structure ◽  
Human Language ◽  
Functional Constraints ◽  
Cognitive Constraints ◽  
Learning Experiment ◽  
Fundamental Properties ◽  
Previous Generation ◽  
Relative Contribution ◽  
Iterated Learning

This paper reviews how the structure of form and meaning spaces influences the nature and the dynamics of the form-meaning mappings in language. In general, in a structured form or meaning space, not all forms and meanings are equivalent: some forms and some meanings are more easily confused with each other than with other forms or meanings. We first give a formalization of this idea, and explore how it influences robust form-meaning mappings. It is shown that some fundamental properties of human language, such as discreteness and combinatorial structure as well as universals of sound systems of human languages follow from optimal communication in structured form and meaning spaces. We also argue that some properties of human language follow less from these fundamental issues, and more from cognitive constraints. We then show that it is possible to experimentally investigate the relative contribution of functional constraints and of cognitive constraints. We illustrate this with an example of one of our own experiments, in which experimental participants have to learn a set of complex form-meaning mappings that have been produced by a previous generation of participants. Theoretically predicted properties appear in the sets of signals that emerge in this iterated learning experiment.

scholarly journals The origins of duality of patterning in artificial whistled languages

2012 ◽  
Vol 4 (4) ◽  
pp. 357-380 ◽  
Author(s):  
Tessa Verhoef
Keyword(s):  
Cultural Transmission ◽  
Cognitive Biases ◽  
Combinatorial Structure ◽  
Basic Design ◽  
Human Language ◽  
Design Features ◽  
Finite Set ◽  
Iterated Learning ◽  
Duality Of Patterning

AbstractIn human speech, a finite set of basic sounds is combined into a (potentially) unlimited set of well-formed morphemes. Hockett (1960) placed this phenomenon under the term ‘duality of patterning’ and included it as one of the basic design features of human language. Of the thirteen basic design features Hockett proposed, duality of patterning is the least studied and it is still unclear how it evolved in language. Recent work shedding light on this is summarized in this paper and experimental data is presented. This data shows that combinatorial structure can emerge in an artificial whistled language through cultural transmission as an adaptation to human cognitive biases and learning. In this work the method of experimental iterated learning (Kirby et al. 2008) is used, in which a participant is trained on the reproductions of the utterances the previous participant learned. Participants learn and recall a system of sounds that are produced with a slide whistle. Transmission from participant to participant causes the whistle systems to change and become more learnable and more structured. These findings follow from qualitative observations, quantitative measures and a follow-up experiment that tests how well participants can learn the emerged whistled languages by generalizing from a few examples.

scholarly journals Amount of Learning and Signal Stability Modulate Emergence of Combinatorial Structure and Iconicity in Novel Signaling Systems

2020 ◽  
Author(s):  
Vera Kempe ◽  
Nikolay Panayotov ◽  
Nicolas Gauvrit ◽  
Sheila J Cunningham ◽  
Monica Tamariz
Keyword(s):  
Language Learning ◽  
Temporal Stability ◽  
Visual Signals ◽  
Combinatorial Structure ◽  
Signal Space ◽  
Signaling Systems ◽  
Signal Stability ◽  
Compositional Structure ◽  
Signal Characteristics ◽  
Iterated Learning

Iterated language learning experiments that explore emergence of linguistic structure in the laboratory vary considerably in methodological implementation, limiting generalizability of findings. Most studies also restrict themselves to exploring the emergence of combinatorial and compositional structure in isolation. Here, we use a novel signal space comprising binary auditory and visual sequences and manipulate amount of learning and temporal stability of these signals. Participants had to learn signals for meanings differing in size, shape and brightness; their productions in the test phase were transmitted to the next participant. Across transmission chains of 10 generations each, Experiment 1 varied how much learning of auditory signals took place, and Experiment 2 varied temporal stability of visual signals. We found that combinatorial structure emerged most reliably with greater amount of learning and when signals were temporally stable. Iconicity emerged with reduced amount of learning, as opportunity for rote-memorization appeared to hamper exploration of the iconic affordances of the signal space. However, emergence of combinatoriality and iconicity in these entirely unfamiliar signaling systems was too fragile to allow for compositional signal-meaning mappings to emerge, so learnability did not improve over the course of transmission. These findings underscore the importance of systematically manipulating training conditions and signal characteristics in iterated learning language learning experiments and suggest that combinatorial structure and iconicity may be a prerequisite for emergence of compositional structure in novel signaling systems.

Can a Skywalker Localize the Midpoint of a Rope?

2021 ◽  
Vol 13 (3) ◽  
pp. 1-23
Author(s):  
Akihiro Monde ◽  
Yukiko Yamauchi ◽  
Shuji Kijima ◽  
Yamashita Masafumi
Keyword(s):  
Distributed Computing ◽  
Mobile Robots ◽  
Line Segment ◽  
Autonomous Mobile Robots ◽  
Location Problems ◽  
Simple Problem ◽  
Impossibility Theorem ◽  
Abstract Model ◽  
Localization Problem ◽  
End Point

This article poses a question about a simple localization problem. The question is if an oblivious walker on a line segment can localize the midpoint of the line segment in a finite number of steps observing the direction (i.e., Left or Right) and the distance to the nearest end point. This problem arises from self-stabilizing location problems by autonomous mobile robots with limited visibility , which is an abstract model attracting a wide interest in distributed computing. Contrary to appearances, it is far from trivial whether this simple problem is solvable, and it is not settled yet. This article is concerned with three variants of the problem with a minimal relaxation and presents self-stabilizing algorithms for them. We also show an easy impossibility theorem for bilaterally symmetric algorithms.

scholarly journals Iconicity and Structure in the Emergence of Combinatoriality

2019 ◽  
Author(s):  
Matthias Hofer ◽  
Roger Philip Levy
Keyword(s):  
Language Evolution ◽  
Virtual Slide ◽  
Design Feature ◽  
Building Blocks ◽  
Developmental Trajectory ◽  
Combinatorial Structure ◽  
Human Language ◽  
Finite Set ◽  
Iterated Learning ◽  
Combinatorial System

One design feature of human language is its combinatorial phonology, allowing it to form an unbounded set of meaningful utterances from a finite set of building blocks. Recent experiments suggest how this feature can evolve culturally when continuous signals are repeatedly transmitted between generations. Because the building blocks of a combinatorial system lack independent meaning, combinatorial structure appears to be in conflict with iconicity, another property salient in language evolution. To investigate the developmental trajectory of iconicity during the evolution of combinatoriality, we conducted an iterated learning experiment where participants learned auditory signals produced using a virtual slide whistle. We find that iconicity emerges rapidly but is gradually lost over generations as combinatorial structure continues to increase. This suggests that iconicity biases, whose presence was revealed in a signal guessing experiment, manifest in nuanced ways. We discuss implications of these findings for different ideas about how biases for iconicity and combinatoriality interact in language evolution.

Study of pointing system for implementation of optical communication of mobile robots

2021 ◽  
Vol 9 (2) ◽  
pp. 91-98
Author(s):  
Darya Stepanova
Keyword(s):  
Visual System ◽  
Mobile Robots ◽  
Optical Communication ◽  
Data Transmission ◽  
High Frequency ◽  
Mutual Influence ◽  
High Accuracy ◽  
System Model ◽  
Extreme Conditions ◽  
Control Loop

Hardware and software solutions for high-precision pointing tasks have found application in various fields of robotics. For mobile robots operating in extreme conditions, pointing of instruments, data transmission systems and navigation devices is a task of prime importance. Using the visual system as a feedback, it is possible to achieve pointing of aircraft embedded instruments with high accuracy. The issues of interest for this work on the development of a high-frequency guidance control loop and its implementation using the visual system as feedback remain relevant for research. In the course of this work, a study was carried out for the use of such systems. Based on the previously derived requirements for the system, the architecture of the pointing system was developed. Next, a variant of the control system implementation was investigated to achieve the required accuracy of instrument pointing. In addition, hardware solution was considered and a system model was built taking into account the mutual influence of the pointing system drives, and with a closed control loop.

A cognitive approach to cumulative technological culture is useful and necessary but only if it also applies to other species

2020 ◽  
Vol 43 ◽  
Author(s):  
Thibaud Gruber
Keyword(s):  
Social Learning ◽  
Cognitive Processes ◽  
Learning Processes ◽  
Cognitive Approach ◽  
Technological Culture ◽  
Social Learning Processes

Abstract The debate on cumulative technological culture (CTC) is dominated by social-learning discussions, at the expense of other cognitive processes, leading to flawed circular arguments. I welcome the authors' approach to decouple CTC from social-learning processes without minimizing their impact. Yet, this model will only be informative to understand the evolution of CTC if tested in other cultural species.

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