Adaptive computing system capable of learning and discovery
First Claim
1. A computing system comprising, in combination,a source of input data comprising k-bit binary message words,a message memory for storing said input data and additional k-bit binary message words,a classifier memory for storing a plurality of classifiers, each of said classifiers being composed of a condition part, an action part, and a strength value,said condition part comprising one or more k-position ternary words each of which specifies a subset of the possible k-bit binary message words, andsaid action part comprising at least one k-position ternary word which at least partially specifies the content of a new message word,matching means for comparing each message word in said message memory with the condition part of each classifier in said classifier memory,means responsive to said matching means for generating new message word whenever each of the ternary words in the condition part of a classifier is satisfied by at least one message in said message memory, andmeans for increasing the strength value associated with a particular classifier whenever said particular classifier generates a new message word to which a further classifier responds by generating a message word.
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Abstract
An electronic computing system capable of learning and discovery employing a language composed of conditional statements called "classifiers" which respond to and operate fixed-length binary words called "messages". Each classifier comprises a condition part which identifies the message(s) to which the classfier responds, and an action part which specifies the content of the generated message which may, in part, be a function of one or more of the input messages. An adaptive algorithm, called the "bucket brigade algorithm", tracks the history of each classifier'"'"'s performance and develops a strength value which serves as a measure of the past usefulness of that classifier in reaching a defined objective. A genetic algorithm generates new classifiers which are based on the strongest of the existing classifiers and which replace the weakest of the existing classifiers.
176 Citations
40 Claims
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1. A computing system comprising, in combination,
a source of input data comprising k-bit binary message words, a message memory for storing said input data and additional k-bit binary message words, a classifier memory for storing a plurality of classifiers, each of said classifiers being composed of a condition part, an action part, and a strength value, said condition part comprising one or more k-position ternary words each of which specifies a subset of the possible k-bit binary message words, and said action part comprising at least one k-position ternary word which at least partially specifies the content of a new message word, matching means for comparing each message word in said message memory with the condition part of each classifier in said classifier memory, means responsive to said matching means for generating new message word whenever each of the ternary words in the condition part of a classifier is satisfied by at least one message in said message memory, and means for increasing the strength value associated with a particular classifier whenever said particular classifier generates a new message word to which a further classifier responds by generating a message word.
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7. A computing system comprising, in combination,
a message store for storing a plurality of k-position binary message words, a classifier store for storing a plurality of classifiers, each of said classifiers comprising a condition part composed of at least one k-position ternary condition word which specifies a subset of possible message words and an action part which at least partially specifies the content of an output message, means for comparing said condition words with said message words, means for assigning an initial strength value to each of said classifiers, means responsive to said comparing means for forming a bid value whenever the specifications contained in the condition part of a given classifier is satisfied by one or more messages in said message store, said bid value being directly related to the current strength value of said given classifier and inversely related to the size of the subset of possible messages specified by the condition part of said classifier, means for producing new set of message words as specified by the action part of those particular classifiers which generated high relative bid values, means for reducing the current strength value assigned to each of said particular classifiers, and means for increasing the current strength value of those classifiers which produced a message word which satisfied the specifications of the condition part of one of said particular classifiers.
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9. An adaptive method for processing input data from an external source into output data having desired characteristics comprising, in combination, the steps of
(a) storing in a message memory of plurality of messages each comprising a sequence of binary digits, at least some of said messages containing information derived from said input data, (b) storing in a classifier memory a plurality of classifier each constituting an instruction governing the performance of a predetermined message translation step and each comprising, in combination, a condition part for identifying a class of said messages in said message memory which are to be translated by said translation step to form result messages, an action part specifying the functional relationship between messages in said class and said result messages, and a strength value; -
(c) performing the message translation steps defined by said classifiers to produce a group of said result messages; (d) replacing the messages stored in said message memory with messages from said group produced by classifiers having higher relative strength values; and (e) increasing the strength value of each classifier which produces a result message which is placed in said message memory and which in turn satisfies the condition part of a classifier to produce a further result message which is placed in said message memory. - View Dependent Claims (10, 11, 12, 13, 14)
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15. An adaptive computer system for processing input data from an external source to yield output data having predetermined characteristics, said system comprising, in combination:
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a message memory for storing messages, each of said messages comprising a unit of information represented as a sequence of binary digits; a classifier memory for storing a plurality of classifiers each consisting of a condition part for specifying the attributes of one or more selected classes of messages stored in said message memory, an action part for specifying the manner in which the messages in said selected classes are to be translated into output messages, and a strength value indicative of the past utility of said classifier; input means for converting said input data from said external source into one or more messages and for storing said messages in said message memory; processing means for performing a plurality of independent procedures each in accordance with a respective one of said plurality of classifiers to generate a collection of result messages, and reward means responsive to selected result messages for increasing the strength value associated with those classifiers which produced said selected result messages. - View Dependent Claims (16, 17, 18, 22, 37, 38, 39, 40)
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19. An adaptive computing system comprising, in combination,
a message memory for storing a plurality of messages, each message being represented by a sequence of binary digits; -
a classifier memory for storing a plurality of classifiers, each such classifier consisting of; a condition part identifying selected messages which are to be read from the message memory and processed into result messages, an action part which specifies the functional relationship between said selected messages and said result messages, and a strength value; and processing means for translating messages in said message store in accordance with each of said classifiers, said processing means including means for increasing the strength value of any classifier which creates a result message which is itself specified by the condition part of a second classifier and translated into a further result message which is placed in said message store. - View Dependent Claims (20, 21, 23, 24, 25)
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26. An adaptive computing system for processing input information from an external source into output information delivered to external utilization means comprising, in combination,
a message memory for storing a plurality of messages, each of said messages comprising a binary sequence of digits, a classifier memory for storing a plurality of classifiers each having a condition part, an action part and a strength value, said condition part specifying the attributes of a class of messages in said message memory which are to be translated into output messages in accordance with information contained in said action part, means establishing a sequence of major machine cycles, processing means operative during each of said major cycles for generating an output message whenever the condition part of any of said classifiers is satisfied by one or more messages in said message memory, means for replacing the messages present in said message memory at the start of a given major cycle with the output messages generated during said given major cycle, input message handling means connected to said external source for placing input messages into said message memory prior to at least one of said major cycles, output message handling means for selecting output messages having predetermined desired characteristics from said message memory and delivering said output messages to said external utilization means, and means for increasing the strength value of each classifier which generates a message which, during the next major cycle, is delivered to said external utilization means or causes the generation of a further output message by satisfying the condition part of a classifier.
Specification