creators_name: Edmonds, B. type: preprint datestamp: 2000-01-28 lastmod: 2011-03-11 08:54:20 metadata_visibility: show title: Towards a Descriptive Model of Agent Strategy Search subjects: cog-psy subjects: comp-sci-art-intel subjects: comp-sci-complex-theory subjects: comp-sci-mach-learn subjects: phil-sci full_text_status: public keywords: induction, strategy, search, computational economics, descriptive modelling, Sonnemans, agent, description, genetic programming, game, auction, modelling methodology, agent-based modelling abstract: It is argued that due to the complexity of most economic phenomena, the chances of deriving correct models from a priori principles are small. Instead are more descriptive approach to modelling should be pursued. Agent-based modelling is characterised as a step in this direction. However many agent-based models use off-the-shelf algorithms from computer science without regard to their descriptive accuracy. This paper attempts an agent model that describes the behaviour of subjects reported by Joep Sonnemans as accurately as possible. It takes a structure that is compatible with current thinking cognitive science and explores the nature of the agent processes that then match the behaviour of the subjects. This suggests further modelling improvements and experiments. date: 1999-09 date_type: published refereed: TRUE citation: Edmonds, B. (1999) Towards a Descriptive Model of Agent Strategy Search. [Preprint] document_url: http://cogprints.org/840/3/tdmass.pdf