A Computational Model of the Coevolution of Lexicon and Syntax
نویسندگان
چکیده
In this paper, a multi-agent computational model is used to simulate the emergence of a compositional language from a holistic signaling system through iterative interactions among heterogeneous agents. Syntax, in the form of simple word order, coevolves with the emergence of the lexicon through self-organization in individuals. We simulate an indirect meaning transference, in which the listener’s comprehension is based on the interaction of linguistic and nonlinguistic information, together with a feedback without direct meaning checking. Homonyms and synonyms emerge inevitably during the rule acquisition. Homonym avoidance is assumed to be a necessary mechanism for developing an effective communication system.
منابع مشابه
Coevolution of lexicon and syntax from a simulation perspective
Whether simple syntax (in the form of simple word order) can emerge during the emergence of lexicon is studied from a simulation perspective; a multiagent computational model is adopted to trace a lexicon-syntax coevolution through iterative communications. Several factors that may affect this self-organizing process are discussed. An indirect meaning transference is simulated to study the effe...
متن کاملCode-Copying in the Balochi Language of Sistan
This empirical study deals with language contact phenomena in Sistan. Code-copying is viewed as a strategy of linguistic behavior when a dominated language acquires new elements in lexicon, phonology, morphology, syntax, pragmatic organization, etc., which can be interpreted as copies of a dominating language. In this framework Persian is regarded as the model code which provides elements for b...
متن کاملModels of EFL Learners’ Vocabulary Development: Spreading Activation vs. Hierarchical Network Model
Semantic network approaches view organization or representation of internal lexicon in the form of either spreading or hierarchical system identified, respectively, as Spreading Activation Model (SAM) and Hi- erarchical Network Model (HNM). However, the validity of either model is amongst the intact issues in the literature which can be studied through basing the instruction compatible wi...
متن کاملEmotion Detection in Persian Text; A Machine Learning Model
This study aimed to develop a computational model for recognition of emotion in Persian text as a supervised machine learning problem. We considered Pluthchik emotion model as supervised learning criteria and Support Vector Machine (SVM) as baseline classifier. We also used NRC lexicon and contextual features as training data and components of the model. One hundred selected texts including pol...
متن کاملExploring the Roles of Horizontal, Vertical, and Oblique Transmissions in Language Evolution
This article proposes an acquisition framework that involves horizontal, vertical, and oblique transmissions. Based on a lexicon–syntax coevolution model, it discusses the relative roles of these forms of cultural transmission on language origin and change. The simulation results not only reveal an integrated role of oblique transmission that combines the roles of horizontal and vertical transm...
متن کامل