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School of Geography

The effect of socio-emotional changes on human mobility and dispersal: Agent Based Modelling of the impact of interactions with ‘outsiders’ on human migration patterns

Supervisors: Dr Alison HeppenstallDr Andrew Evans, Dr Penny Spikins (University of York)


Human evolution has been marked by significant changes in social complexity, which Gowlett, Gamble and Dunbar (2011) infer relate to key phases occurring 2.6-1.6 million, 1.5 to 0.4 million and 300-25 thousand bp. Whilst the former phase is marked by larger community sizes, the second by more advanced theory of mind and the subsequent social means of integrating smaller units into larger populations, the latter is a time of ever larger communities and relationally based organisation between many different individuals. The progressive evolution of socio-emotional capacities has been increasingly recognised as a basis for such complexity (Coward and Gamble 2008, Spikins et al 2010, also Gowlett, Gamble and Dunbar 2010, Spikins 2012) nonetheless the precise mechanisms through which changes in socio-emotional capacities influence wider social patterns remain underexplored.

The link between changes in socio-emotional capacities and resultant wide scale social and material changes is not necessarily intuitive. Although several key stages in empathising abilities have marked the departure between the evolution of human and other primate minds and the emergence of uniquely human ways of interacting (Decety et al 2012) the link between such stages and observed behaviours can be elusive.  A capacity for emotional awareness is for example key to human social relationship (Steklis and Lane 2012) yet this capacity is not readily linked to any particular archaeological signature.

One key human adaptation has been a widening of oxytocin responses to dampen threat systems and allow empathetic interactions with outsiders, non-kin or non-group members (Decety et al 2012). A consequence of this change is the capacity to form new trusting relationships with people we have rarely or never met, supported by social emotions which are felt more strongly in such scenarios. The significance of an extension of empathy to ‘outsiders’ (or at least non-kin or group members) can be seen not only in a modern tendency to be altruistic to strangers, eg by giving blood, but in the tendency for individuals in small scale societies to be generous to strangers in economic games. The potential evolutionary advantages of an ability to extend our empathy to empathise or care about people we don’t usually live with or see as kin as aptly demonstrated in the widespread evidence for networks of trusting relationships with high degrees of give and take between non-kin which provide a social buffer in times of resource stress, both amongst modern hunter-gatherers (Weissner 2002, 2009) and by analogy those of the Upper Palaeolithic (Whallon 2006). Genuinely altruistic relationships from the basis for collaboration in hunter-gatherers such as the Hadza (Apicella 2012). Weissner notes an example for the Jo’husani when half of the group members at a time of famine at NaeNae were able to travel to visit distant friends allowing all the group to survive, having built up relationships based on trust and high degrees of give and take, bolstered by gift giving (Weissner 2009 check figures). Yet the timing of emergence of this key adaptation remains to be discussed and its relationship to elements of the archaeological record such as patterns of dispersal is unexplored.

Key Research Questions

What are the potential effects of socio-emotional capacities on early human dispersal patterns?

Can an agent-based model be created that can model the effects of interactions with non-kin or group members?

Can the model be used to evaluate whether this is a potential driver for early human dispersal patterns?


This PhD will involve the following methodologies:


  1. Agent-based modelling (Crooks and Heppenstall, 2012):  this is an individual-based modelling approach that allows actors to be created within a computer environment and assigned hetereogeneous characteristics.  These individuals can be a part of groups or entirely autonomous of others. 
  2. Behavioural models: Review of different behavioural models and incorporation into the agent-based model.  Dr Penny Spikins at York will provide supervision concerning the behavioural dynamics.
  3. Quantitative methods: How best to examine the results?  Part of the PhD will be spend learning and applying basic and advanced spatial analysis methods (including Geographical Information Systems). 

Academic and previous experience required;

Undergraduate or postgraduate qualification in one of the following areas:  Geography, Archaeology or Computer Science.

If you have other related experience/background but are still interested in the project, please get in contact with us.

Training to be provided (specific to the project and generic)

The following options are open to PhD students:

  • University run courses ranging from general PhD to specific statistical courses
  • School of Geography Master’s courses:  the student will have access to basic and advanced Java programming, spatial statistic, Geocomputation and GIS courses.
  • Support will be given to external courses that will be invaluable to the student.

Research environment (cluster and wider research community;

  • The student will be a member of the Centre for Spatial Analysis and Policy research group.  Through this group the student will have access to a variety of researchers with expertise in different areas.
  • The Multi-Agent and Social Simulation (MASS) group is based in the School; this is a group of researchers who are experts in the development of agent-based models. 
  • The PhD supervisors are experts in this area and will provide support when required.

Background or further reading/bibliography

Agent-based Models

Crooks, A.T. and Heppenstall, A.J. (2012) An Introduction to Agent-based Models.  In Heppenstall, A.J., Crooks, A.T., See, L.M. and Batty, M.  (eds) Agent-based Models of Geographical Systems.  Springer: Dordrecht

Railsback, S.F. and Grimm, V. (2012) Agent-based and Individual-Based Modelling: A Practical Introduction.  Princeton University Press

Torrens, P. (2010) Agent-based Models and the Spatial Sciences.  Geography Compass 4/5: 428 – 448.

Malleson, N., See, L. M., Evans, A. J. and Heppenstall, A. J. (2012). . Implementing comprehensive offender behaviour in a realistic agent-based model of burglary Simulation: Transactions of the Society for modelling and Simulation International. 88(1) 50 – 71. DOI: 10.1177/003754971038124


Apicella, C. L., Marlowe, F. W., Fowler, J. H., and Christakis, N. A., Social Networks and cooperation in hunter-gatherers, Nature 481, 497-501

McNamara, J., Barta, Z., From Hage, L., and Houston, A. I. 208. The evolution of choosiness and cooperation, Nature 451: 189-192

Decety, J. Norman, G. J., Berntson, G. C., and Cacioppo, J. T. 2012. A nuerobehavioural evolutionary perspective on the mechanisms underlying empathy. Progess in Neurobiology 98, 38-48

Gamble, C., Gowlett, J and Dunbar, R. 2011. The social brain and the shape of the Palaeolithic, Cambridge Archaeological Journal 21, 01, 115-136.

Laland, K. N., Odling-Smee, J and Myles, S. 2010. How culture shaped the human genome: bringing genetics and the human sciences together, Nature Reviews 11, 137-148

Hazelwood, L. and Steele, J. 2004. Spatial dynamics of human dispersals: Constraints on modelling and archaeological validation, Journal of Archaeological Science, 31: 669-679

Coward, F and Gamble, C. 2008. Big brains, small worlds: material culture and the evolution of mind. Philosophical Transactions of the Royal Society B. 363. 1499. 1969-1979.

Gamble, C. 2009. Human display and dispersal: A case study from biotidal Britain in the Middle and Upper Pleistocene, Evolutionary Anthropology 18: 144-156

Steklis, H. D., and Lane, R. D., 2012. The unique human capacity for emotional awareness: psychological, neuroanatomical, comparative and evolutionary perspectives, in Emotions of Animals and Human: Comparative Perspectives, eds. S. Watanabe and S. Kuczaj. Springer. pp 165-205


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