The utility of reinforcement learning in predation of Batesian mimics
Anastasios Tsoularis · International Journal of Computer Aided Engineering and Technology · 2009
In this article, the focus is on modelling the predation of Batesian mimics using reinforcement learning methodology. Essentially, it is proposed that the predator be modelled as a learning automaton aided by reinforcement algorithms to select palatable prey for consumption and avoid unpalatable ones. A tentative connection between reinforcement learning and the theory of dynamic programming and optimal control is also considered. The paper concludes by offering some ideas for future research in this area.