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BACKGROUND
Simulating the
Evolution of Language
The communication between autonomous agents, be
they robots or simulated virtual agents, has recently attracted the
interest of researchers from different fields. In engineering, the design
and evaluation of communication systems is interesting due to its practical
applications for agent-agent interaction and also for human-agent and
human-robot communication (e.g. Lauria et al., 2002) . For cognitive
scientists, the development of computational models for the evolution of
language permits the investigation of the role of sensorimotor, cognitive,
neural and social factors in the emergence and establishment of
communication and language (Cangelosi & Parisi, 2002).
Studies on the emergence of communication are often
based on synthetic methodologies such as adaptive behaviour and multi-agent
systems (Steels, 1997; Kirby, 2002). A group of autonomous agents interact
via language games to exchange information about the external environment.
Their coordinated communication system is not externally imposed by the
researcher, but emerges from the interaction between agents. In such
models, the levels of detail of the representation of the agents and of
their environment can vary significantly. This constitutes a continuum
between abstract point models, at one end, and situated, embodied robots at
the other. At one extreme, only the essential communicative properties of
the agents and the environment are simulated. For example, the environment
can consist of a list of abstract “meanings”, and the agent consists of a
function, or rule set, that maps these meanings to signals (e.g. Kirby,
2001; Oliphant, 1999). This approach is useful when one wants to study the
dynamics of the auto-organization of lexicons and syntax and its dependence
on single, pre-identified factors. An intermediate approach to language
evolution is based on grounded simulation models (Harnad, 1990). The
agents’ environment is modelled with a high degree of detail upon which
emergent meanings can be directly grounded. Each simulated agent has a set
of sensorimotor, cognitive and social abilities that allow it to build,
through interaction, a functional representation of the environment and use
it to communicate (e.g. Cangelosi, 2001; Cangelosi & Harnad, 2000;
Hazlehurst & Hutchins, 1998). This type of models supports the
investigation of the interaction amongst various abilities of the agents
for the emergence of language and the grounding of communication symbols in
the environment and the agent’s behaviour. At the other end of the
continuum, the communicative behaviour of embodied and situated robots
results from the dynamical interaction between its physical body, the
nervous and cognitive system and the external physical and social
environment (Beer, 1995). For example, robots can interact and communicate
among themselves (e.g. Steels & Vogt, 1997; Quinn, 2001), with virtual
Internet agents (Steels, 1999) and with humans (Steels & Kaplan, 2000).
Such an approach permits the study of the interaction between the different
levels of a behavioural system, i.e. from sensorimotor coordination to
high-level cognition and social interaction.
The research developed with the present EPSRC
grant has mostly focused on the use of grounded simulation models for
investigating the evolution of language. In particular, the simulation
models have addressed the transfer of grounding in connectionist models,
the role of sensorimotor and neural factors in supporting the emergence of
syntax in simulate agents and in evolutionary robots. In addition, part of
the research has utilized multi-agents systems based on abstract, symbolic
agents. The critical analyses of the contribution that these simulations,
together with existing literature models, have brought to the field of language
evolution modelling has also been the focus of the grant through the
editing of the book “Simulating
the Evolution of Language” (Springer Verlag, 2002) by the PI Angelo Cangelosi.
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