Automata networks;
Linguistic conventions;
Working memory;
Sharp transition;
EVOLUTION;
LANGUAGE;
D O I:
10.1007/s12559-015-9371-7
中图分类号:
TP18 [人工智能理论];
学科分类号:
081104 ;
0812 ;
0835 ;
1405 ;
摘要:
This work attempts to give new theoretical insights into the absence of intermediate stages in the evolution of language. In particular, a mathematical model, based on automata networks, is proposed with the purpose to answer a crucial question: How a population of language users can reach agreement on linguistic conventions? To describe the appearance of drastic transitions in the development of language, an extremely simple model of working memory is adopted: at each time step, language users simply lose part of their word memories according to a forgetfulness parameter. Through computer simulations on low-dimensional lattices, sharp transitions at critical values of the parameter are described.
机构:
Shahid Beheshti Univ, Dept Phys, Tehran 19839, IranShahid Beheshti Univ, Dept Phys, Tehran 19839, Iran
Rabbani, Fereshteh
Khraisha, Tamer
论文数: 0引用数: 0
h-index: 0
机构:
Cent European Univ, Dept Network & Data Sci, Nador U 9, H-1051 Budapest, HungaryShahid Beheshti Univ, Dept Phys, Tehran 19839, Iran
Khraisha, Tamer
论文数: 引用数:
h-index:
机构:
Abbasi, Fatemeh
Jafari, Gholam Reza
论文数: 0引用数: 0
h-index: 0
机构:
Shahid Beheshti Univ, Dept Phys, Tehran 19839, Iran
Cent European Univ, Dept Network & Data Sci, Nador U 9, H-1051 Budapest, HungaryShahid Beheshti Univ, Dept Phys, Tehran 19839, Iran