Autonomous humanoid cognitive systems
First Claim
1. A computer system for implementing decisions of an autonomous decision system in an environmental situation, comprising:
- a) at least one computer processor structured and arranged to process data;
b) at least one computer storage device structured and arranged to store data on a storage medium;
c) at least one input computer processor structured and arranged to provide temporally-incremental input data about a series of said environmental situations; and
d) at least one concrete-situation computer processor structured and arranged to process data regarding said temporally-incremental input data about said series of said environmental situations to provide a temporally-incremental series, respectively, of “
present”
concrete self-situation representations of said respective environmental situations, whereini) each said self-situation representation comprises a self representation and a set of event representations, each said event representation being represented specifically spacio-temporally relative to said self representation, and each said event representation including(1) a behavioral-type designation selected from a set of behavioral-type designations, each said behavioral-type designation of said set of behavioral-type designations being associated with a set of incremental behavioral self-tendencies for determining incrementally-predicted self-situation representations from a said presented self-situation representation; and
(2) a set of current-behavior designations associated with each said event representation specifying the current behaviors of each said event representation; and
e) wherein said system enables implementing decisions of an autonomous decision system in an environmental situation.
2 Assignments
0 Petitions
Accused Products
Abstract
Disclosed are computer systems with intelligent or autonomous decision systems which include means for determining relevancy, i.e., the threats to and opportunities of the autonomous decision system. Also disclosed are such autonomous decision systems using an efficient ontology to interact sociably with humans, including the use of natural languages and bonding. The desired “whether concrete is included in abstract” computation system is enhanced by the ontology system using categorizing of natural objects using as primitives a set of self tendencies suitable, when hierarchically assigned to objects, to do incremental simulation of “future” situations (including such objects) from a presented situation. Using such primitives and computation system, planning, learning, languaging, etc., are efficiently accomplished.
-
Citations
21 Claims
-
1. A computer system for implementing decisions of an autonomous decision system in an environmental situation, comprising:
-
a) at least one computer processor structured and arranged to process data; b) at least one computer storage device structured and arranged to store data on a storage medium; c) at least one input computer processor structured and arranged to provide temporally-incremental input data about a series of said environmental situations; and d) at least one concrete-situation computer processor structured and arranged to process data regarding said temporally-incremental input data about said series of said environmental situations to provide a temporally-incremental series, respectively, of “
present”
concrete self-situation representations of said respective environmental situations, whereini) each said self-situation representation comprises a self representation and a set of event representations, each said event representation being represented specifically spacio-temporally relative to said self representation, and each said event representation including (1) a behavioral-type designation selected from a set of behavioral-type designations, each said behavioral-type designation of said set of behavioral-type designations being associated with a set of incremental behavioral self-tendencies for determining incrementally-predicted self-situation representations from a said presented self-situation representation; and (2) a set of current-behavior designations associated with each said event representation specifying the current behaviors of each said event representation; and e) wherein said system enables implementing decisions of an autonomous decision system in an environmental situation. - View Dependent Claims (2, 3)
-
-
4. A computer system for implementing natural language functions in a humanoid autonomous decision system, comprising:
-
a) at least one computer processor structured and arranged to process data; b) at least one computer storage device structured and arranged to store data on a storage medium; i) wherein said data comprises non-linguistic discrete data-types and, conforming to each of said discrete non-linguistic data-types, a set of non-linguistic discrete data elements; and c) at least one input computer processor structured and arranged to provide information about current circumstances of the humanoid autonomous decision system; d) at least one output computer processor structured and arranged to implement decisions of the humanoid autonomous decision system; and e) at least one relevance computer processor structured and arranged to provide information regarding the relevance to the humanoid autonomous decision system of said current circumstances, comprising i) at least one self-representation computer processor structured and arranged to process data regarding “
self”
to provide at least one “
self”
representation,ii) at least one structured-situation computer processor structured and arranged to process data regarding said current circumstances to provide a first non-linguistic structured “
self”
-situation representation,iii) at least one relational-situation computer storage device structured and arranged to provide data regarding a set of hierarchically-organized, relevant, non-linguistic relational “
self”
-situations, andiv) at least one inclusional computer processor structured and arranged to process data to determine inclusions of a said first non-linguistic structured “
self”
-situation within said non-linguistic relational “
self”
-situations to determine any relevance of said first structured “
self”
-situation to a said “
self”
of said relevance means,v) wherein said data regarding said set of hierarchically-organized, relevant, non-linguistic relational “
self”
-situations includes data regarding(1) a set of hierarchically-organized problem relational “
self”
-situations, and(2) in association with essentially each of said problem relational “
self”
-situations, a set of hierarchically-organized plan relational “
self”
-situations; andf) at least one type-linking computer storage device structured and arranged to provide data regarding i) respectively linking essentially each said discrete data-type of said humanoid autonomous decision system with a respective word/phrase category of a first natural language, and ii) respectively linking selected words/phrases of each said linked word/phrase category of said first natural language with respective said discrete data elements of each said discrete data-type so linked with a said linked word/phrase category; and g) at least one data transformation computer processor structured and arranged to process data regarding a first communication to be made by said humanoid autonomous decision system to transform a specified set of non-linguistic data elements into a said first communication in said first natural language, comprising i) at least one identification computer processor structured and arranged to process data regarding identifying which of said discrete data elements of said discrete data-types is to form part of said first communication, ii) at least one snippet computer processor structured and arranged to process data regarding selecting natural-language snippets for pointing to the said categories of said natural-language corresponding to whichever of said discrete data-types includes each said discrete data element which is to form part of said first communication, iii) at least one vocabulary computer processor structured and arranged to process data regarding selecting a word/phrase of said natural-language corresponding to each said discrete data element which is to form part of said first communication, and iv) at least one grammar computer processor structured and arranged to process data regarding producing from the grammar practices of said natural language and from said snippet selections and from said word/phrase selections said first communication in said natural language. - View Dependent Claims (5)
-
-
6. A computer system for implementing first natural language interpretation functions in a humanoid autonomous decision system interpreting incoming first natural language from another, comprising:
-
a) at least one computer processor structured and arranged to process data; b) at least one computer storage device structured and arranged to store data on a storage medium i) wherein said data comprises non-linguistic discrete data-types and, conforming to each of said discrete non-linguistic data-types, a set of non-linguistic discrete data elements; c) at least one type-linking computer storage device structured and arranged to provide data regarding i) respectively linking essentially each said discrete data-type of said humanoid autonomous decision system with a respective word/phrase category of said first natural language, and ii) respectively linking selected words/phrases of each said linked word/phrase category of said first natural language with respective said discrete data elements of each said discrete data-type so linked with a said linked word/phrase category; and d) at least one input computer processor structured and arranged to provide input information about characteristics of said incoming natural language sufficient to identify each vocabulary element, snippet type for each said element, and grammatical function for each said element; e) at least one translation computer processor structured and arranged to process data regarding said input information to provide a non-natural-language concrete circumstance interpretation of said input information; and f) at least one relevance computer processor structured and arranged to provide information regarding the relevance to the humanoid autonomous decision system of said circumstance interpretation, comprising i) at least one relational-situation computer storage device structured and arranged to provide data regarding a set of hierarchically-organized, relevant, non-linguistic relational “
self”
-situations, andii) at least one inclusional computer processor structured and arranged to process data to determine inclusions of said non-natural-language concrete circumstance interpretation within said non-linguistic relational “
self”
-situations to determine any relevance of said non-natural-language concrete circumstance interpretation a said “
self”
of said at least one relevance computer processor,iii) wherein said data regarding said set of hierarchically-organized, relevant, non-linguistic relational “
self”
-situations includes data regarding(1) a set of hierarchically-organized problem relational “
self”
-situations, and(2) in association with essentially each of said problem relational “
self”
-situations, a set of hierarchically-organized plan relational “
self”
-situations. - View Dependent Claims (7)
-
-
8. A computer system for machine learning from an environmental situation in an autonomous decision system, comprising:
-
a) at least one computer processor structured and arranged to process data; b) at least one computer storage device structured and arranged to store data on a storage medium; c) at least one input computer processor structured and arranged to provide temporally-incremental input data about a series of said environmental situations; and d) at least one concrete-situation computer processor structured and arranged to process data regarding said temporally-incremental input data about said series of said environmental situations to provide a temporally-incremental series, respectively, of “
present”
concrete self-situation representations of said respective environmental situations, whereini) each said self-situation representation comprises a self representation and a set of event representations, each said event representation being represented specifically spacio-temporally relative to said self representation, and each said event representation including (1) a behavioral-type designation selected from a set of behavioral-type designations, each said behavioral-type designation of said set of behavioral-type designations being associated with a set of incremental behavioral self-tendencies for determining incrementally-predicted self-situation representations from a said presented self-situation representation; and (2) a set of current-behavior designations associated with each said event representation specifying the current behaviors of each said event representation; and e) wherein said system provides machine learning from an environmental situation in an autonomous decision system. - View Dependent Claims (9)
-
-
10. A computer system for an entertainment system, comprising:
-
a) at least one computer simulation processor structured and arranged to process data regarding a user-selected “
world”
-representation containing user-selected spacio-temporally located “
object”
-representations to provide incremental simulation-stepping of said “
world”
-representation;b) at least one natural-language computer interface structured and arranged to process data for providing a natural-language interface for user selection of non-natural-language characteristics of a said “
object”
-representation;c) at least one placement computer interface structured and arranged to process data for providing an interface for user placement of a said “
object”
-representation into said “
world”
-representation;d) at least one computer interface structured and arranged to process data for providing an interface for placement into said “
world”
-representation, as a said “
object”
-representation, of an autonomous decision system;e) wherein said autonomous decision system comprises i) at least one representation computer processor structured and arranged to process data essentially from said “
world”
-representation for presenting a selected self-situation (for said autonomous decision system) representation, said presented self-situation representation comprising a self representation and a set of event representations, each said event representation being represented specifically spacio-temporally relative to said self representation, andii) at least one prediction computer processor structured and arranged to process data for determining the representations of a set of incrementally-predicted self-situations, predicted as incremental consequences from said presented self-situation representation; iii) wherein said at least one prediction computer processor comprises said computer simulation processor.
-
-
11. A machine computational-processing method, for providing current simulated-emotion expression in at least one simulated-humanoid autonomous decision system having at least one ability to assess a set of environmental circumstances, comprising the steps of:
-
a) storing in such at least one simulated-humanoid autonomous decision system planning data providing plan capability to such at least one simulated-humanoid autonomous decision system; b) using information about such set of environmental circumstances of such at least one simulated-humanoid autonomous decision system and such plan capability, computing at least one current planning selection; c) using information about such at least one current planning selection, computing at least one current planning status; d) using information about such at least one current planning status, computing current simulated-emotion source data; and e) using such current simulated-emotion-source data, computing current simulated-emotion status. - View Dependent Claims (12)
-
-
13. A machine computational-processing method, for implementing decisions of at least one autonomous decision system in environmental situations, such at least one autonomous decision system having at least one input system for providing temporally-incremental input data about a series of such environmental situations, comprising the steps of:
-
a) computationally processing such temporally-incremental input data about such series of such environmental situations to provide a temporally-incremental series, respectively, of “
present”
concrete self-situation representations of such respective environmental situations, whereini) each such “
present”
concrete self-situation representation comprises a self representation and a set of event representations, each such event representation being represented spacio-temporally relative to each such self representation, wherein each such event representation comprises(1) at least one behavioral-type designation selected from a set of behavioral-type designations, each such at least one behavioral-type designation of such set of behavioral-type designations being associated with a set of incremental behavioral self-tendencies for determining incrementally-predicted self-situation representations from each such “
present”
concrete self-situation representation, and(2) a set of current-behavior designations associated with each such event representation specifying the current behaviors of each such event representation; b) computationally processing data regarding at least one such “
present”
concrete self-situation representation of such respective environmental situation to determine the representations of a set of incrementally-predicted self-situations, predicted as incremental consequences from such at least one “
present”
concrete self-situation representation;c) storing data for hierarchical planning comprising i) a hierarchical set of n problem representations, and ii) m plan-sets of hierarchical subgoal representations, each said plan-set of hierarchical subgoal representations being associated with at least one of said set of n problem representations; and d) computationally comparing such data for hierarchical planning with such data about each such “
present”
concrete self-situation representation and each such incrementally-predicted self-situation to determinei) at least one self-relevancy of each such presented self-situation representation, and ii) at least one self-relevancy of each such incrementally-predicted self-situation representation; e) wherein any threat to and any opportunity of such at least one autonomous decision system may be determined. - View Dependent Claims (14, 15, 16)
-
-
17. A machine computational-processing method, for implementing natural language functions in at least one simulated humanoid autonomous decision system, comprising the steps of:
-
a) storing in at least one computational storage system data comprising non-linguistic discrete data-types and, conforming to each of such discrete non-linguistic data-types, a set of non-linguistic discrete data elements; b) storing in at least one computational storage system data i) respectively linking essentially each such discrete data-type of such simulated-humanoid autonomous decision system with a respective word/phrase category of at least one first natural language, and ii) respectively linking selected words/phrases of each such linked word/phrase category of such at least one first natural language with respective such discrete data elements of each such discrete data-type so linked with a such linked word/phrase category; c) using information about at least one set of current circumstances of such at least one simulated-humanoid autonomous decision system, computationally determining at least one relevance to the simulated-humanoid autonomous decision system of such current circumstances; d) using information about such at least one relevance, computationally specifying at least one set of relevant such non-linguistic discrete data elements; and e) using such specification of such at least one set of relevant such non-linguistic discrete data elements, computationally determining at least one first communication to be made by such simulated-humanoid autonomous decision system to transform such specified set of non-linguistic discrete data elements into such at least one first communication in such first natural language; f) wherein such step of computational determining comprises i) computationally processing data regarding identifying which of such discrete data elements of such discrete data-types is to form part of such at least one first communication, ii) computationally processing data regarding selecting natural-language snippets for pointing to the such categories of such natural-language corresponding to whichever of such discrete data-types includes each such discrete data element which is to form part of such at least one first communication, iii) computationally processing data regarding selecting a word/phrase of such natural-language corresponding to each such discrete data element which is to form part of such at least one first communication, and iv) computationally processing data regarding producing from grammar practices of such natural language and from such snippet selections and from such word/phrase selections such at least one first communication in such natural language.
-
-
18. A machine computational-processing method for implementing first natural language interpretation functions in at least one simulated-humanoid autonomous decision system interpreting incoming first natural language from at least one other, comprising the steps of:
-
a) storing in at least one computational storage system data comprising non-linguistic discrete data-types and, conforming to each of such discrete non-linguistic data-types, a set of non-linguistic discrete data elements; b) storing in at least one computational storage system data i) respectively linking essentially each such discrete data-type of such simulated-humanoid autonomous decision system with a respective word/phrase category of at least one first natural language, and ii) respectively linking selected words/phrases of each such linked word/phrase category of such at least one first natural language with respective such discrete data elements of each such discrete data-type so linked with a such linked word/phrase category; c) computationally processing such incoming natural language sufficiently to provided data identifying each vocabulary element, snippet type for each such element, and grammatical function for each such element; d) computationally processing such identifying data to provide a non-natural-language concrete circumstance interpretation of such incoming natural language; and e) computationally determining at least one relevance to such at least one simulated-humanoid autonomous decision system of such circumstance interpretation; f) wherein such computational determining comprises i) storing data regarding a set of hierarchically-organized, relevant, non-linguistic relational “
self”
-situations, andii) computationally processing to determine inclusions of such non-natural-language concrete circumstance interpretation within such non-linguistic relational “
self”
-situations to determine any relevance of such non-natural-language concrete circumstance interpretation to such at least one simulated-humanoid autonomous decision system,iii) wherein such data regarding such set of hierarchically-organized, relevant, non-linguistic relational “
self”
-situations includes data regarding(1) a set of hierarchically-organized problem relational “
self”
-situations, and(2) in association with essentially each of said problem relational “
self”
-situations, a set of hierarchically-organized plan relational “
self”
-situations. - View Dependent Claims (19, 20, 21)
-
Specification