Abstract: Computing systems and computer-implemented methods for specifying distributed computation. The systems and methods utilize computer-readable code causing a computer to engage in reversible, self-organizing hierarchical space-like computation that create information. At least one sensor and effector adapted to react to an environment external to the computer/computing system can create information based on an input from or “experience” with that environment.

Abstract: Computing systems and computer-implemented methods for specifying distributed computation. The systems and methods utilize computer-readable code causing a computer to engage in reversible, self-organizing hierarchical space-like computation that create information. At least one sensor and effector adapted to react to an environment external to the computer/computing system can create information based on an input from or “experience” with that environment.

Abstract: An improved computer and system thereof which monitors the state of an array of sensors. In the preferred embodiment, these sensors monitor a physical or internal condition and have two states. The invention establishes a time window and identifies which of the sensors have changed state within the time window. The sensors which have changed state are then grouped into a "tuple" which is used by an operator to analyze the operations of the environment being studied using such methods as co-exclusion. Through selective control of the length of the time window, changes in two or more sensors permit co-exclusion properties to be inferred.

Abstract: An artificial intelligence system which utilizes a unique technique for storing data, analyzing data, and reducing the complexity of data is disclosed. The technique involves identifying "world" states that have a unique exclusive relationship. The identification of these unique states considerably reduces the complexity of the world under study. Furthermore, the identified unique states are useful in combination with any way the system has to affect the world under study. These identified unique states, when placed in a hierarchical scheme, further reduces the complexity of the world under study.

Abstract: A computer system which learns or assimilates its experience into a hierarchical arrangement. The current set of events, represented as a general directed graph of nodes and arcs, is incorporated into a memory. After each observation or input, the resulting graph is analyzed to determine if any cycles exist. Each cycle is reduced to a single node. This collapsing of the graph creates a hierarchial arrangement of the past events. Each successive level of hierarchy, by burying the details, is a more generalized model of the past experiences. In this manner, not only are computational and memory requirements reduced, but, the computer system will learn from past events which to permit use in such applications as robotics or general operator inquiry and interaction.