Language Emergence: a Self-Organized Model using Indirect Meaning Transference

Tao Gong, Jinyun Ke, James W. Minett, William Wang

Department of Electronic Engineering, City University of Hong Kong,
Kowloon, Hong Kong

50005488@student.cityu.edu.hk, jyke@ee.cityu.edu.hk, minett@ee.cityu.edu.hk

Abstract

With the introduction of computational modeling into linguistic study,
many plausible models (Ke et al 2002; Kirby 1998, 2002; Batali 1998;
Cangelosi 2002) of communication among a group of homogeneous agents
have been presented, which investigate the emergence of both
unstructured and structured utterances, and are based on both learning
and evolutionary mechanisms.  However, the use of direct meaning
transference in supervised learning, ignoring the evolution of syntax,
and not studying the effect of social structure on language acquisition
all limit the authenticity of these models.  Based on Wray's emergent
scenario (Wray, 2002), we assume that language emerged during an
iterative process of decomposition, combination and cognizing the
environment.  In this paper, a computational model on language
emergence, following this view, is presented to address limitations
stated above. 

In this model, co-evolution and convergence of lexicon and simple syntax
(word order) at the protolanguage level and a transition from holistic
utterances without internal structure to compositional language with a
dominant word order are driven by strategies of self-organization (e.g.,
rule activation, rule-based decision-making and competition inspired by
Classifier Systems (Holland 2001)).  Indirect meaning transference, in
which interaction of linguistic and non-linguistic information (cues,
meanings extracted from environmental information) determines meaning
interpretation, together with a primitive feedback mechanism without
direct meaning checking are implemented.  The cues are not necessarily
always reliable; nevertheless, the language acquired in this model can
still be used to robustly express meanings not present in the immediate
environment of the agents (displacement) and to accurately interpret the
meanings of utterances even under wrong cues. 
 
Due to the lack of explicit access to other agents' languages and
agents' use of free search to detect recurrent patterns, homophony and
synonymy are inevitable in this model.  With unreliable cues, at the
protolanguage level, homophone avoidance might be necessary to avoid
ambiguity in communication during the transition from a holistic
signalling system to a compositional language. 

Exploratory research on the effect of social structure on language
acquisition, based on network theory, is introduced.  A social structure
with popular agent(s), common in primate societies and which might have
been common in early human societies as well as, is studied.  In such
social structure, it seems that there is an optimal popularity rate of
the popular agent for a language to develop effectively in the
population.  Further study of social structure using more complex
network structures (e.g., scale-free network, small world network) is a
promising direction that we expect to make progress in during the coming
months. 

Finally, other promising future work, such as introducing heterogeneity
in agents' abilities in language processing, and simulating
communications among more than 2 agents, is identified. 

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