The Modeling And Analyzing For The Random Search Behavior With Collective Constraints

Animal in foraging presents the characteristics of random search, such as Brownian Walks, Levy Walks, intermittent search strategy et al. However, animal groups in foraging not only present the characteristics of random search, but also the collective characteristics like consistency and cohesion. Most previous work on animal foraging always concentrated on the former, but ignored the latter. Therefore, for explaining the foraging behavior of animal group more clearly, it is necessary to model and analyze random search behavior with the collective constraint.Firstly, environment-driven social force model is proposed to model complex foraging behavior described above. The environment and conspecific effects are two fundamental inducements to the complex behavior of animal group. Social force is used to quantify these two effects. The decision of animal individual is depended on the results of force analysis. The simulation results present the individual Levy walk patterns and the consistency and cohesion of the entity group. In addition, the individual attributes and the parameters of social forces are investigated to analyze the effect on the behavior. The analysis results show the partition of perception area in individual attributes is core to influence the search efficiency and collective characteristics.In addition, the intermittent search mechanism with collective constraint based on Levy strategy is proposed to search a moving target. The social force model with collective constraint we proposed is combined with intermittent search strategy. The searcher implements the intermittent search strategy. The forces from interaction between searchers keep them in group. The results show that this mechanism are more suitable for the search task with large spatial scales and small group scales than the random search mechanism without group constraint, and have a better performance when the target is acute.