Daniel Ladley

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This paper reviews the Zero Intelligence methodology for investigating markets. This approach models individual traders, operating within a market mechanism, who behave without strategy in order to determine the impact of the market mechanism and consequently the effect of trader behaviour. The paper considers the major contributions and models within this(More)
We introduce a distinction between algorithm performance and algorithm competence and argue that bio-inspired computing should characterize the former rather than the latter. To exemplify this, we explore and extend a bio-inspired algorithm for collective construction influenced by paper wasp behavior. Despite its being provably general in its competence,(More)
This is the very first draft, still warm and in its infancy. Please comment as much as you like (and as much as it deserves) but do not quote. ACKNOWLEDGEMENT We are indebted to Sanjit Dhami, Ali Al-Nowaihi, Kalvinder Shields and Kevin Lee for their comments on an earlier version of the paper. We are solely responsible for the remaining deficiencies.(More)
Work within the field of artificial life has as history of exploring the ways in which locally constrained interactions between the elements of a system can give rise to organised behaviour at the level of the ensemble. Here we study the effect of constraining cooperative , competitive and communicative interactions within a market by embedding it within a(More)
The majority of market theory is only concerned with centralised markets. In this paper, we consider a market that is distributed over a network, allowing us to characterise spatially (or temporally) separated markets. The effect of this modification on the behaviour of a market with a heterogeneous population of traders, under selection through a genetic(More)
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