Models that can represent the range of objects from sub-atomic particles to planets have a major obstacle preventing them from practical use. If they can act with such diversity they may also require a very complex set of functions to describe their behavior. In Process and Reality, Alfred North Whitehead proposes a philosophical model he terms Actual Entities which this study brings over to the realm of computer science. By doing so, a method for computationally modeling objects at all levels may be found. This book focuses on providing the reader with an overview of Actual Entities and lays the groundwork for their use in computation. A method for extracting the functionally computable behavior of real world objects is then addressed. This method uses Artificial Neural Networks as learning agents which observe a series of behavioral snapshots and then infer the rules behind these interactions. This book is intended for those interested in the theories of A. N. Whitehead and particularly the practical applications thereof. It is also intended for computer scientists interested in models for objects that possess interactions that are too complex to formulate by hand.