Abstract: Method and system for modeling of complex systems using a two-sorted reasoning system. Information is received by Distributed Feature Extraction Processors. A first level of reasoning is performed on the information by Distributed Regular Reasoning Processors. A second reasoning process is performed on the information by Distributed Situation Reasoning Processors, which use a Functional Fabric configured to analyze the information received and use functions to modify previous inferences. Client applications allow for viewing and manipulating both reasoning systems and their associated information.

Abstract: Method and system for modeling of complex systems using a two-sorted reasoning system. Information is received by Distributed Feature Extraction Processors. A first level of reasoning is performed on the information by Distributed Regular Reasoning Processors. A second reasoning process is performed on the information by Distributed Situation Reasoning Processors, which use a Functional Fabric configured to analyze the information received and use functions to modify previous inferences. Client applications allow for viewing and manipulating both reasoning systems and their associated information.

Abstract: A system for deriving ontologies to support inferencing with changing context, including changes of time. Embodiment of the invention use a unique system for modeling context and the interactions among multiple contexts in order to compute functions that can modify ontologies for presentation to a reasoning system. A parallel unique system allows previous inferences to be retrospectively modified based on newly derived ontological semantics. The system allows for the creation of new ontological elements and auditable models of agency and cause. It can be implemented using methods that delay evaluation until semantic interpretation is required, either at the ontological or inferential level.

Abstract: Method and system for modeling of complex systems using a two-sorted reasoning system. Information is received by Distributed Feature Extraction Processors. A first level of reasoning is performed on the information by Distributed Regular Reasoning Processors. A second reasoning process is performed on the information by Distributed Situation Reasoning Processors, which use a Functional Fabric configured to analyze the information received and use functions to modify previous inferences. Client applications allow for viewing and manipulating both reasoning systems and their associated information.

Abstract: A system for deriving ontologies to support inferencing with changing context, including changes of time. Embodiment of the invention use a unique system for modeling context and the interactions among multiple contexts in order to compute functions that can modify ontologies for presentation to a reasoning system. A parallel unique system allows previous inferences to be retrospectively modified based on newly derived ontological semantics. The system allows for the creation of new ontological elements and auditable models of agency and cause. It can be implemented using methods that delay evaluation until semantic interpretation is required, either at the ontological or inferential level.