Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.750162
Title: The diffusion of culture : computational and statistical models of social learning and cultural transmission
Author: Ounsley, James P.
ISNI:       0000 0004 7234 4152
Awarding Body: University of St Andrews
Current Institution: University of St Andrews
Date of Award: 2017
Availability of Full Text:
Access from EThOS:
Full text unavailable from EThOS. Restricted access.
Access from Institution:
Abstract:
Culture is a hugely important process in the evolution of humans and many non-human animals. Through the formation of long lasting traditions, culture provides an extragenetic inheritance mechanism that can facilitate rapid behavioural adaptation to novel environments. This can ultimately alter the selection pressures acting on different phenotypes including those that underlie cultural transmission itself, i.e. the mechanisms of social learning. Understanding culture poses many challenges for researchers due to the complex nature of interacting biological processes at multiple organisational and temporal scales. In this thesis I investigate some of these complexities through the integration of different theoretical and statistical modelling approaches, and argue that rich models are particularly important for the study of culture. In chapters 3 & 4 I use an evolutionary agent-based model to study the functional value and cultural significance of strategically copying from other individuals based on particular cues, such as age or payoff. I find that a bias to copy the successful can provide substantial adaptive advantages, potentially outweighing other strategic considerations such as when to engage in social learning. I also demonstrate that the strength of selection on social learning strategies is closely linked to the cultural diversity within a population. In chapters 5 & 6 I study the mechanisms of learning and how social influences can impact decision making. In chapter 5 I model the behaviour of nursery children and chimpanzee groups when solving a complex task and identify clear species differences in the importance of different forms of learning on decision making. Finally, in chapter 6 I use an agent-based model to examine the influence of population structure on the spread of novel behaviour. I demonstrate that, contrary to infectious disease type models, when learning occurs through operant conditioning, highly clustered network structures promote cultural transmission rather than hinder it.
Supervisor: Ruxton, Graeme Douglas ; Laland, Kevin Neville Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.750162  DOI: Not available
Keywords: HQ783.O8 ; Social learning--Mathematical models
Share: