Received: by alpheratz.cpm.aca.mmu.ac.uk id NAA23646 (8.6.9/5.3[ref pg@gmsl.co.uk] for cpm.aca.mmu.ac.uk from b.edmonds@mmu.ac.uk); Mon, 5 Mar 2001 13:45:20 GMT Message-ID: <3AA397CC.29075FAE@mmu.ac.uk> Date: Mon, 05 Mar 2001 13:42:36 +0000 From: Bruce Edmonds <b.edmonds@mmu.ac.uk> Organization: Centre for Policy Modelling X-Mailer: Mozilla 4.76 [en] (WinNT; U) X-Accept-Language: en To: JOM announcements list <jom-emit-ann@mmu.ac.uk> Subject: New JoM-EMIT paper: Cultural evolution of "guiding behaviour" ... by Gianluca Baldassarre Content-Type: text/plain; charset=us-ascii Content-Transfer-Encoding: 7bit Sender: b.edmonds@mmu.ac.uk Precedence: bulk Reply-To: JOM-EMIT@sepa.tudelft.nl
Cultural evolution of "guiding
criteria" and behaviour in a
population of neural-network agents
by Gianluca Baldassarre
Abstract
1 - Introduction
2 - Methods
2.1 - The environment and the task
2.2 - Individual learning
2.3 - Cultural transmission
3 - Results and interpretation
4 - Related work
5 - Conclusion and future work
Acknowledgements
References
Abstract
An important form of cultural evolution involves individual
learning of behaviour by the members of a population of agents
and cultural transmission of learned behaviour to the following
generations. The selection of behaviours generated in the process
of individual learning requires some "guiding criteria". As with
behaviour, guiding criteria can be innate or originate from
individual or social learning. Guiding criteria play a fundamental
role in cultural evolution because they strongly contribute to
determine the behaviours that will enter the pool of cultural traits
of the population. This work presents a computational model that
investigates the nature and function of some forms of "guiding
criteria" in the cultural evolution of a population of agents that
learn and adapt to the environment using neural networks. The
model focuses on the interplay of individual learning and cultural
transmission of behaviour and those forms of guiding criteria.
The model contributes to clarify the nature and role in culture
evolution of the guiding criteria studied. Also, within the
assumptions of the model, it shows that the cultural transmission
of behaviour is more effective than the transmission of the
guiding criteria.
Keywords: Multi-agent simulation, neural networks, cultural
evolution, cultural transmission, reinforcement learning, imitation,
behaviour, guiding criteria, values, evaluations.
Available at:
http://www.cpm.mmu.ac.uk/jom-emit/2001/vol4/baldassarre_g.html
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