Design Perceptive

The use of potential fields in path planning is well established in the field of artificial intelligence.  In general, a physical space is modelled by a field of vectors where goals are attractors and obstacles are repellers.  Determining the direction to move for a mobile robot is then a matter of following the vector.

As intelligent agents, humans are constantly being pulled about by contending forces.  Our own beliefs and intentions betray us when acting as motivators to our own behavior.  I may horribly detest flying to the point of aversion, but the desire to flee conflict or danger may override that aversion and cause me to get on an airplane.  We tend to manage these conflict in a number of ways, including prioritization of goals.  Where one goal might be a low priority now, might become high priority later by virtue of time or other factors.

I am proposing the use of potential fields as a model for complex motivational system.  Under this model, behavioral states are modeled as attractors and repellers much like goals and obstacles.  Rather than modelling a physical space defined by the x,y,z dimensions, I propose a  space that defines relevancy.  In short, potential fields provide a means for modeling relevancy.  It also provides a means of dealing with conflicting goals.