Interestingly, there are many similarities of complex phenomena in these disciplines and some general models for their analysis, such as optimal foraging theory or game theory, which have been successfully applied to fields other than their origin. Conversely, it is reasonable to expect that many complex phenomena which we find in nature are based on simple local mechanisms, which induce system complexity as an emergent property of repeated local interactions. Interestingly, biological systems have evolved properties which are particularly wanted in computer sciences, as for instance concurrency, adaptability, robustness, and self-organisation. The aim of SocialLab is to design computer models that can explain this potential of biological processes and are applicable to related tasks in computing. Though SocialLab was originally designed and used to investigate the evolution of cooperation and division of labour in collaboration with prof.
All agents move and interact in their virtual niche consisting of a two-dimensional grid space.
Each grid cell has local spatial properties, such as the maximum number of individuals it can carry. In this virtual world, agents compete with others for virtual resources, such as space and food. Their survival and reproductive success crucially depends on sufficient accomplishment and management of these resources. A motivation network is a biologically inspired model for reasoning in autonomous agents, which mimics basic mechanisms of animal behaviour. The main idea is that decisions of animals are based on temporary priorities regarding different behavioural drives, which are triggered by inputs from sensors and internal states, and evaluated in respect to genetically determined response patterns.