Angelo Cangelosi (Principal
Turner (PhD student)
Marocco (visiting PhD student)
Harnad (External advisor, University of Southampton - UQAM Montreal)
Parisi (CNR Rome)
(Universita' di Genova, Italy)
Thomas Riga (now at
University of Plymouth)
Barbara Giolito (Universita' Piemonte Orientale,
aim of this research is to investigate and develop computational models of
the origins and evolution of language and communication. The modelling
approach mainly uses artificial neural networks, genetic algorithms and
evolutionary robotics to simulate evolving populations of communicating
autonomous agents. Some simulations also use an English parser model to
study the emergence of syntactic universals under cognitive contraints.
Various simulation programs have been developed and used for numerous
experimental investigations. These were designed to investigate some of the
biological, neural, and adaptive mechanisms that lead to the evolution of language.
This research studies have significantly contributed to (a) develop new
neural network models for the acquisition of categories through grounded
symbols, (b) identify the sensorimotor basis of syntactic categories such
as nouns and verbs, (c) investigate the evolution of optimal word orders
under working menory constraints, (d) test Deacon's hypothesis on the
co-evolution of language and brain structures and (e) identify different
Baldwinian phenomena in language evolution. The research has potential
applications in Robotics and Artificial intelligence (e.g. evolutionary
robotics) for the development of adaptive and self-organising algorithms
for communication in multi-agent and multi-robot systems. It is also of
interest to the scientific community of Computational Neuroscience (e.g.
new applications of synthetic brain imaging) and Cognitive Science (e.g.
relationship between sensorimotor knowledge and linguistic categories,
grounding of symbols in cognitive models). The simulation programs and the
publications are available on the world wide web.