Equine and Animal Cognition Reference Database -- Query Results

Hemelrijk, C. K. (2000). Towards the integration of social dominance and spatial structure. Anim. Behav., 59(5), 1035–1048. Abstract: My aim was to show how individual-oriented (or artificial life) models may provide an integrative background for the development of theories about dominance by including effects of spatial structure. Dominance interactions are thought to serve two different, contrasting functions: acquisition of high rank and reduction of aggression. The model I present consists of a homogeneous virtual world inhabited by artificial agents whose actions are restricted to grouping and dominance interactions in which the effects of winning and losing are self-reinforcing. The two functions are implemented as strategies to initiate dominance interactions and the intensity of aggression and dominance perception (direct or memory based) are varied experimentally. Behaviour is studied by recording the same behavioural units as in real animals. Ranks appear to differentiate more clearly at high than at low intensity of aggression and also more in the case of direct than of memory-based rank perception. Strong differentiation of rank produces a cascade of unexpected effects that differ depending on which function is implemented: for instance, a decline in aggression, spatial centrality of dominants and a correlation between rank and aggression. Insight into the origination of these self-organized patterns leads to new hypotheses for the study of the social behaviour of real animals. https://references.equine-behaviour.de/show.php?record=863
Hemelrijk, C. K. (2002). Understanding Social Behaviour with the Help of Complexity Science (Invited Article). Ethology, 108(8), 655–671. Abstract: Abstract In the study of complexity, a new kind of explanation has been developed for social behaviour. It shows how patterns of social behaviour can arise as a side-effect of the interaction of individuals with their social or physical environment (e.g. by self-organization). This development may influence our ideas about the direct causation and evolution of social behaviour. Furthermore, it may influence our theories about the integration of different traits. This new method has been made possible by the increase in computing power. It is now applied in many areas of science, such as physics, chemistry, sociology and economics. However, in zoology and anthropology it is still rare. The major aim of this paper is to make this method more generally accepted among behavioural scientists. https://references.equine-behaviour.de/show.php?record=5200

Abstract: My aim was to show how individual-oriented (or artificial life) models may provide an integrative background for the development of theories about dominance by including effects of spatial structure. Dominance interactions are thought to serve two different, contrasting functions: acquisition of high rank and reduction of aggression. The model I present consists of a homogeneous virtual world inhabited by artificial agents whose actions are restricted to grouping and dominance interactions in which the effects of winning and losing are self-reinforcing. The two functions are implemented as strategies to initiate dominance interactions and the intensity of aggression and dominance perception (direct or memory based) are varied experimentally. Behaviour is studied by recording the same behavioural units as in real animals. Ranks appear to differentiate more clearly at high than at low intensity of aggression and also more in the case of direct than of memory-based rank perception. Strong differentiation of rank produces a cascade of unexpected effects that differ depending on which function is implemented: for instance, a decline in aggression, spatial centrality of dominants and a correlation between rank and aggression. Insight into the origination of these self-organized patterns leads to new hypotheses for the study of the social behaviour of real animals.

https://references.equine-behaviour.de/show.php?record=863

Abstract: Abstract In the study of complexity, a new kind of explanation has been developed for social behaviour. It shows how patterns of social behaviour can arise as a side-effect of the interaction of individuals with their social or physical environment (e.g. by self-organization). This development may influence our ideas about the direct causation and evolution of social behaviour. Furthermore, it may influence our theories about the integration of different traits. This new method has been made possible by the increase in computing power. It is now applied in many areas of science, such as physics, chemistry, sociology and economics. However, in zoology and anthropology it is still rare. The major aim of this paper is to make this method more generally accepted among behavioural scientists.