Evolving Collective Behaviors With Diverse But Predictable Sensor States

Artificial evolution of collective behaviors can be implemented in different ways. Here, we extend the approach of Hamann (2014). The underlying concept is that the brain is permanently trying to predict future perceptions and a state of well-being is a state that allows for precise predictions (Friston, 2010). Striving for maximal prediction success needs to be complemented by a force that implements curiosity and exploration. In this abstract we present an extended method diverse-prediction that rewards not only for correct predictions but also for each visited sensory state.