Animat Navigation Using Landmarks Navigation of Simulated Animals Inspired by Bees

Abstract

Machine Learning techniques have made large advancements in previously challenging problems. A common problem with these methods is that they are very specialised on their specific field problem and it requires a lot of work to apply the methods on a new problem. A solution to this general issue is Artificial General Intelligence( AGI). This is an AI that is able to identify any problem and find a solution. Animals often needs to navigate complex environments to survive. This master thesis tries to implement a homing navigation model, used by bees to find food by remembering places relative positions to landmarks, in the general animat model. The model consists of using sensors that detect landmarks relative position to the animat. The model shows a small improvement when compared against Q-learning. The result suggests that the animat model can produce more sophisticated methods of navigation but further research needs to be conducted to explore its limits.