Many have put forth architectures that facilitate cognition, learning, memories, and information processing, but it is not sufficient to create a completely autonomous Artificially Intelligent System (AIS). An overall AIS architecture framework, along with a knowledge and cognitive ontology are required in order to facilitate a fully autonomous, cognitive, self-aware, self-assessing, AIS. Such a system must include architectures and methodologies for managing such cognitive processes. Described here is an AIS processing and management framework called the Polymorphic, Evolutionary, Neural Learning and Processing Environment (PENLPE). This AIS processing and management framework allows dynamic adaptation of the structural elements of the cognitive system, providing the abilities to add and prune cognitive elements as necessary in the AIS evolution. PENLPE accommodates a variety of memory classes and algorithm methods. The basic building blocks of each are the Artificial Cognitive Neural Framework (ACNF), as well as methodologies and architectures for Memory, Decision, Rules, Learning, Reasoning, Decision, and Failure Management.
展开▼
