A Brain-like Cognitive Process with Shared Methods
This is an incremental improvement for researchers in cognitive modeling and AI, focusing on refining existing methods rather than introducing new paradigms.
The paper tackles the problem of refining a brain-inspired cognitive model by updating localized processes and introducing a new entropy-style equation, with results including redefining functional levels in human vernacular and enhancing architecture with features.
This paper describes a new entropy-style of equation that may be useful in a general sense, but can be applied to a cognitive model with related processes. The model is based on the human brain, with automatic and distributed pattern activity. Methods for carrying out the different processes are suggested. The main purpose of this paper is to reaffirm earlier research on different knowledge-based and experience-based clustering techniques. The overall architecture has stayed essentially the same and so it is the localised processes or smaller details that have been updated. For example, a counting mechanism is used slightly differently, to measure a level of 'cohesion' instead of a 'correct' classification, over pattern instances. The introduction of features has further enhanced the architecture and the new entropy-style equation is proposed. While an earlier paper defined three levels of functional requirement, this paper re-defines the levels in a more human vernacular, with higher-level goals described in terms of action-result pairs.