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Agent-Based ModellingAgent-based modelling is a form of individual-based population model where individual simulants maintain internal data states and have senses that allow them to detect the environment they find themselves in. For a primate simulation they need a standard behavioural repertoire, a set of capabilitieis, and their goal is to maximise personal fitness. This should be sufficient to generate observed behaviours and we certainly plan to try and match the outcomes of our modelling with field-based observational data.
This figure illustrates the SimAgent system showing individual agents, their field of view and hearing ranges. Decision trees are used to allow the agent to decide on what to do in the next step depending on its internal state and sensory data. The internal state includes measures of energy balance, social rank and fatigue. Sensory data reveals the likely presense of food, conspecifics, and predators.
Current visualisation techniques are usually rather basic although there are systems that allow 3D display and the technology will ultimately be linked with the locomotor simulations to provide a realistic depiction of individual and community activity. In particular in the Virtual Plio-Pleistocene Project we propose to produce a realistic reconstruction of the conditions in place during this key period of human evolution so that we can provide a workbench for testing the various theories that explain the divergence of the chimp and human lineages. |
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Email: William.Sellers@manchester.ac.uk
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