Dynamic Models for Intention (Goal-Directedness) Are Required by Truly Intelligent Robots

Intelligent behavior is characterized by flexible and creative pursuit of endogenously defined goals. Intentionality is a key concept by which to link brain dynamics to goal-directed behavior, and to design mechanisms for intentional adaptations by machines. Evidence from vertebrate brain evolution and clinical neurology points to the limbic system as the key forebrain structure that creates the neural activity which formulate goals as images of desired future states. The behavior patterns created by the mesoscopic dynamics of the forebrain take the form of hypothesis testing. Predicted information is sought by use of sense organs. Synaptic connectivity of the brain changes by learning from the consequences of actions taken. Software and hardware systems using coupled nonlinear differential equations with chaotic attractor landscapes simulate these functions in free-roving machines learning to operate in unstructured environments.