Data processing: artificial intelligence – Knowledge processing system – Knowledge representation and reasoning technique
Reexamination Certificate
1999-09-14
2001-07-31
Davis, George B. (Department: 2122)
Data processing: artificial intelligence
Knowledge processing system
Knowledge representation and reasoning technique
C707S793000, C707S793000, C707S793000, C707S793000, C707S793000
Reexamination Certificate
active
06269356
ABSTRACT:
This invention relates to expert systems and natural language parsers.
BACKGROUND OF THE INVENTION
Expert systems are computer systems that are used to store large amounts of information on a particular topic in a computer database and are designed to respond to queries from a user to provide information about a particular problem. For example, there are expert systems that are used to guide boats through a harbor. Such an expert system contains information in a database that relates to the heights of bridges and the depths of channels in the harbor. A user can query this system on what route it should take with a boat having certain dimensions.
One drawback of these expert systems is that if a user's query asks for information not contained in the data base specifically about that subject, the expert system cannot provide any information. It cannot create ideas and it cannot solve problems by analogy.
SUMMARY OF THE INVENTION
This invention disclosure is about human creativity and problem solving. Its about duplicating human creativity and problem solving using a computer program; and its about telling how this is done so that users can query a computer system for ideas and solutions to their problems.
It is believed that this invention captures the process used by humans to create new ideas and solve problems. It does this by understanding how humans use the English Language to process information by reducing the English Language into actions, subjects, and objects; it understands that the world has many systems that share a tremendous likeness to one another; and, it understands that all system are arranged in an orderly fashion as specified in the hierarchical “Experience Databases.”
This invention takes as its input, English Language statements and breaks them down so that they can be processed against “Experience Databases.” These “Experience Databases” symbolically represent systems in the world in hierarchical format. This hierarchical format recognizes that most systems are formed by a series of functions and processes. Within each function (a function is made up of processes) is an English like statement formed as an action (verb) and two nouns (subject and object)—See
FIG. 1
as an example of verbs and nouns formatted in a hierarchical database structure representing a tree—this is called the tree.exp (experience) database and referred to as an “Experience Database.”
In the search for ideas and solutions, this invention sorts an input problem and goal statement in such a way that it can select the appropriate “Experience Databases” to begin the search for an idea or solution. These selected “Experience Databases” serve as a basis to make the correct symbolic substitutions to develop the right analogies so that the correct choice of ideas and answers can be made.
In particular, in one embodiment of the invention, a computer program receives an input statement including a description of the problem and a goal statement. For example, “The beavers destroyed the bark. Save the tree.” The computer program determines that the word “bark” represents an object of the verb repair, which is associated with the word “save” in the problem statement. The computer program then looks up the work “bark” in the tree Experience Database. The program determines that the “bark” entry in the tree Experience Database is at the second hierarchical level in the data base and that its function is to “protect” the tree. The program also finds that the tree Experience Database has no “repair” function for bark. The computer program then consults a second data base, for example the human Experience Database. It looks for an entry at the second hierarchical level whose function is to “protect” the human, which is the entry corresponding to “skin”. The computer program locates the entry in the human Experience Database that corresponds to the repair function for skin: “Transplant skin to damaged location.” The program then substitutes the word “bark” for the word “skin” in the above sentence to result in a solution to the problem: “Transplant bark to damaged location.” This solution can then be stored in the tree Experience Database so that if the same problem arises again the computer program will not have to create the solution a second time.
The difference between this invention and others is that it uses verbs and nouns (the world is made of actions and objects) to process information, much as humans do, to create ideas and solve problems using formatted “Experience Databases.” It further knows that humans must work subconsciously to understand that by learning one system (economic system for example) it can connect to other systems (using verbs as the connecting factor) to make substitutions and analogies to create ideas and find solutions in other systems (electrical system for example).
This invention is intended to be used by everyone who has the need to create new ideas or solve problems. New ideas or solving problems are dependent on the number of “Experience Databases” at the computer program's disposal. Although, with a limited number of “Experience Databases,” results may be less of an idea or solution. This would be analogous to asking a child for answers versus asking an adult.
Unlike other inventions in the field of “Expert Systems,” this invention knows how to search unrelated data to find corresponding information that may generate the idea or solve the problem. In this invention disclosure, the computer program generates ideas by finding analogies. The analogy that solves a particular problem is the solution.
This invention is a high level computer program that can create new ideas and solve a broad range of problems. It does this through the word analysis of a user inputted problem statement (an English sentence) and a goal declaration (most often a verb phrase). The computer program analyzes the problem statement and goal declaration looking for key words that fall into the classification of: an Action Maker (subject); an Action (primary verb); and Action Taker (object). Each word (either subject or object) is referenced to dictionary data which has been previously categorized. For example, the word bark is in the plant category and further divided into the sub category of tree.
The word categories are referenced to what is called “Experience databases.” Given the problem statement “The beavers destroyed the bark” and “Save the tree,” the computer program begins the solution process, through analysis of each word in the problem and goal statements, starting with bark. It finds the relationship “protect-(bark,tree),” read as “bark protect tree,” in the (tree.exp) “Experience Database.”
To find an analogy or idea, the computer program notes the “protect” verb in the above relation and begins a search of other “Experience Database” looking for this same verb. The Databases that are searched are based on the logical analysis of the problem statement and goal declaration statements. From this analysis, the (human.experience) database is searched looking for a “protect” verb relation. Since there could be many “protect” verb relations within an experience database, the computer program uses a technique called leveling and selects the “protect(skin, human)” relationship, read as “skin protect human” in the (human.experience) database as the analogy to bark. Once the analogy has been determined, the next phase in the solution process begins by looking for things that have to do with skin and repair in the (human.experience) database. The reason the computer program looks for a repair function is based on the analysis of the problem and goal statements. Note that the two words in these statements “destroyed and save” suggest that skin needs to be repaired. But it is not really the skin that needs repair, but bark, and so the computer program makes the appropriate substitution and states that a solution to the problem could be to “Transplant bark to damaged location.” This is the solution that was used to save the tree from destruction by the beavers, and is the same soluti
Davis George B.
Roper & Quigg
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