Data processing: artificial intelligence – Neural network – Learning task
Reexamination Certificate
2000-08-18
2003-07-01
Davis, George B. (Department: 2121)
Data processing: artificial intelligence
Neural network
Learning task
Reexamination Certificate
active
06587846
ABSTRACT:
BACKGROUND—FIELD OF INVENTION
This invention relates to the process of programming the rules governing the use of affective language into a computer, allowing a passive detection mode, along with an active simulation of affective language in an AI mode.
BACKGROUND—DESCRIPTION OF PRIOR ART
Language simulation of an ethical nature has remained an elusive goal for researchers in the field due to the complexities involved in simulating affective language in general. Fortunately, such an achievement has finally been achieved with the development of the power pyramid hierarchy (FIGS.
1
through
10
). A direct outcome of the power pyramid hierarchy is the formulation of the power pyramid definitions, simulating emotionally-charged language in a form programmable into a computer. Through the aid of these schematic definitions, the logical consequences of the power pyramid hierarchy are programmed directly into a computer, serving in applications calling for the rapid decoding of motivational parameters. The computer further utilizes these decoded results to produce a language simulation of its own, allowing for an ethically based simulation of artificial intelligence.
The concept of artificial intelligence (AI) refers to language simulated using a computer. The prevailing standard in the field is the deductive inference machine, which employs deductive reasoning to establish original conclusions from a standard battery of logical premises. The product of years of research by ICOT (The Institute of New Generation Computer Technology) the deductive-inference machine uses information stored in a regional database to deductively draw fresh conclusions not literally contained in the data. A major drawback to this deductive format, however, is a basic restriction limiting conclusions to premises immediately at hand.
An alternate form of reasoning (known as induction) is much better suited to an ethical simulation of AI, formally gathering together the best available evidence, in order to draw the most probable conclusion from the sum total of facts. In contrast to deductive reasoning, the conclusions derived through inductive reasoning are never absolutely certain, although the uncertainties of the physical world give inductive reasoning the clear advantage in such a problem-solving mode. According to such an inductive model, each individual builds up a mental model of reality over a lifetime, forming a master template for all current experiences. When expectations match surroundings, a general sense of security is reached. A mismatch leads to a surprised reaction, followed by investigative behavior. An ethically based AI computer is similarly equipped with its own formal map of reality, employed in an analogous detection and matching function. The logistics of the power pyramid hierarchy rightfully enter the picture at this juncture, serving as the foundation for the first inductive system for decoding and simulating affective language. The logical attributes of the power pyramid definitions provide a formal model of motivational behavior, allowing a decoding of the motivational parameters of a given verbal interchange. On the basis of this determination, the computer devises counter-response of its own, effectively simulating a sense of motivation in the verbal interaction.
OBJECTS AND ADVANTAGES
The Inductive Inference Affective Language Analyzer (hereafter abbreviated IIALA) makes extensive use of parallel processing, where various aspects of a complex problem are handled simultaneously, minimizing the computational bottleneck plaguing sequential processing. The number of parallel processor complexes equals the sum-total of power pyramid definitions (for a grand total of 320), a feasible number even by today's design standards. These processor complexes are further organized in a hierarchial fashion, mirroring the stepwise architecture of the power pyramid hierarchy. This hierarchial arrangement takes full-advantage of the strict transformational logic of the power pyramid hierarchy, eliminating much of the redundancy certain to occur in any convincing language simulation. The greatest degree of complexity involves programming at the most basic (personal) levels of the power pyramid hierarchy, the remaining higher authority levels extending naturally upon this elementary foundation.
The most appropriate unit of input is necessarily the sentence, for the power pyramid definitions are analogously organized in the form of a dual sentence structure. With a design schematic specifying a parallel array of 320 dedicated processor complexes, each individual complex employs parallel processing to determine the relative degree of correlation between an input (target) sentence and its matching power pyramid definition template. The matching process scrutinizes the various grammatical elements of a given sentence, statistical correlating these specifics to a given power pyramid definition. The verb tense, the plurality and person of the nouns/pronouns etc. are all scrutinized according to pre-set criteria. Each processor complex then calculates the sum-total of correct matches, yielding the relative probability that a given sentence matches a particular power pyramid definition. The processor complex yielding the highest overall rating is singled out as the most probable solution to the power pyramid definition matching procedure.
The context of the interaction is further taken into account through the aid of a feedback circuit, the priority of the individual microprocessor complexes preemptively weighted on the basis of preceding deliberations. Each power pyramid definition is composed of both past (as well as present) design components, establishing context as a further critical feature in the detection procedure. The IIALA retains in long-term storage a record of every relevant experience with a given individual or situation. On this contextual basis, the master control unit selectively weights the individual processor complexes according to a record of both past (as well as current) behavior patterns. In this respect, the IIALA is exquisitely sensitive to variations in personality Oust as humans are instinctively so) satisfying yet a further prerequisite of Turing's test (the ultimate standard for evaluating such a system).
REFERENCES:
patent: 6157913 (2000-12-01), Bernstein
patent: 2002/0069220 (2002-06-01), Tran
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