The Synthetic Modeling of Language Origins

Steels, Luc

doi:10.1075/eoc.1.1.02ste

Cited by 259 publications

(161 citation statements)

References 45 publications

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“…A new field, evolutionary linguistics, was born with a specific focus (understand the origins of language and meaning), a specific hypothesis (language is a complex adaptive system), and a specific methodology (construct artificial systems as a way to develop and test theories). An overview of earlier work in this field can be found in [5] and more recent work in [6]. Several recent collections of papers [7][8][9] provide additional source material.…”

Section: Communication Communication Communicationmentioning

confidence: 99%

“…One of the major difficulties is that grammaticalization is strongly grounded in many aspects of human culture and embodiment and these aspects are very difficult to incorporate in artificial systems. (5). We need to understand how populations of agents can self-organize a shared repertoire of discrete building blocks grounded in a continuous physical medium and how a combinatorial system can arise from these building blocks.…”

Section: Horizontal and Vertical Transmissionmentioning

confidence: 99%

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Evolving grounded communication for robots

Steels

2003

Trends in Cognitive Sciences

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297

180

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The computational and robotic synthesis of The computational and robotic synthesis of The computational and robotic synthesis of The computational and robotic synthesis of language evolution is emerging as a new language evolution is emerging as a new language evolution is emerging as a new language evolution is emerging as a new exciting field of research. The objective is to exciting field of research. The objective is to exciting field of research. The objective is to exciting field of research. The objective is to come up with precise operational models of come up with precise operational models of come up with precise operational models of come up with precise operational models of how communities of agents, equipped with a how communities of agents, equipped with a how communities of agents, equipped with a how communities of agents, equipped with a cognitive apparatus, a sensori-motor system, cognitive apparatus, a sensori-motor system, cognitive apparatus, a sensori-motor system, cognitive apparatus, a sensori-motor system,

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Section: Communication Communication Communicationmentioning

confidence: 99%

Section: Horizontal and Vertical Transmissionmentioning

confidence: 99%

Evolving grounded communication for robots

Steels

2003

Trends in Cognitive Sciences

Self Cite

297

180

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“…From this perspective there is a clear account of how language use determines semantics through an emergent process resulting from multiple interactions between individuals, each adopting the epistemic stance and updating their semantics by conditioning within a probabilistic representational model as outlined above. Indeed there is a growing literature on agent-based simulation studies in which simple probabilistic models of concepts are shown to converge across a population (Steels 1997;Steels and Belpaeme 2005;Eyre and Lawry 2014). Nonetheless, one might ask of such approach, why do individuals choose to adopt the epistemic stance, as opposed to an alternative representational model, given that, as admitted, there is no claim as to the objective existence of precise boundaries?…”

Section: The Uncertain Threshold Model Of Vaguenessmentioning

confidence: 99%

Vagueness and Aggregation in Multiple Sender Channels

Lawry

James

2017

Erkenn

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Vagueness is an extremely common feature of natural language, but does it actually play a positive, efficiency enhancing, role in communication? Adopting a probabilistic interpretation of vague terms, we propose that vagueness might act as a source of randomness when deciding what to assert. In this context we investigate the efficacy of multiple sender channels in which senders choose assertions stochastically according to vague definitions of the relevant words, and a receiver then aggregates the different signals. These vague channels are then compared with Boolean channels in which assertions are selected deterministically based on classical (crisp) definitions. We show that given a sufficient number of senders, a linear stochastic channel outperforms Boolean channels when performance is measured by the expected squared error between the actual value described by the senders and the receiver's estimate of it based on the signals they receive. The number of senders required for vague channels to be at least as accurate as Boolean channels is shown to be a decreasing function of the size of the language i.e. the number of description labels available to the senders. Vague channels are then shown to be robust to transmission error provided the error rate is not too large. In addition, we investigate the behaviour of both Boolean and vague channels for a parametrised family of distributions on the input values. Finally, we consider optimal vague channels assuming a fixed number of senders and show that, provided there are more than two senders, a vague channel can be found that outperforms the optimal Boolean channel. In this context, we show that for channels with relatively low numbers of senders S-curve production functions are optimal.

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“…While some defend the innateness of Language and thus the role of genetic mutations in its evolution, Steels [11] defends that language corresponds to a Self-organising phenomena like the ones observed in chemical and biological processes. Furthermore language develops subject to big pressures of the environment, such as limited time for articulation of words, and acoustically adverse environments.…”

Section: Imitation Games: Language and Musicmentioning

confidence: 99%

A Connectionist Architecture for the Evolution of Rhythms

Martins

Miranda

2006

Lecture Notes in Computer Science

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Abstract. In this paper we propose the use of an interactive multi-agent system for the study of rhythm evolution. The aim of the model proposed here is to show to what extent new rhythms emerge from both the interaction between autonomous agents, and self-organisation of internal rhythmic representations. The agents' architecture includes connectionist models to process rhythmic information, by extracting, representing and classifying their compositional patterns. The internal models of the agents are then explained and tested. This architecture was developed to explore the evolution of rhythms in a society of virtual agents based upon imitation games, inspired by research on Language evolution.

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The Synthetic Modeling of Language Origins

Abstract: This paper surveys work on the computational modeling of the origins and evolution of language. The main approaches are described and some example experiments from the domains of the evolution of communication, phonetics, lexicon formation, and syntax are discussed.

Cited by 259 publications

References 45 publications

Evolving grounded communication for robots

Evolving grounded communication for robots

Vagueness and Aggregation in Multiple Sender Channels

A Connectionist Architecture for the Evolution of Rhythms

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