# US 2017/0010589 A1 · Pseudo-genetic meta-knowledge artificial intelligence systems and methods > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2017/0010589 A1 - Document ID: US20170010589A1 - Status: Published application - Kind: A1 - Application number: 15/069,527 - Filed: 2016-03-14 - Published: 2017-01-12 - Earliest claimed: 2012-05-02 - Assignees: Ether Dynamics Corporation - Applicants: Ether Dynamics Corporation - Inventors: Dominic de Anda Fast - Web page: https://patentgrep.com/patent/US20170010589A1 ## CPC - G06N 5/02: Knowledge representation; Symbolic representation - G05B 13/0265: {the criterion being a learning criterion} - G06N 3/006: based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO] - G06N 3/126: Evolutionary algorithms, e.g. genetic algorithms or genetic programming - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS - G05B: CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS (systems for controlling or regulating non-electric variables G05D; systems for regulating electric or magnetic variables G05F; control devices or systems insofar as characterised by mechanical features only G05G) ## Abstract Systems and methods for artificially intelligent physical and virtual actors including pseudo-genetic information and configured to retain meta-knowledge are described. The actors are adapted with unique behavioral and physical attributes which may independently evolve over time. The attributes may include reproduction based attributes which direct how, when, and with whom the actor reproduces and may be subject to mutation and reproductive forces. The attributes may include evaluation attributes which dictate when and how each actor evaluates their performance. The evaluation attributes may also be subject to mutation and reproductive forces. The attributes may consider meta-knowledge which is a reflection of information gathered by an actor. What and how much meta-knowledge is collected may also be expressed as one or more evolvable attributes. ## Claims ### Claim 1 An autonomous actor apparatus, the apparatus comprising: a sensor configured to detect information about the autonomous actor apparatus and an environment in which the autonomous actor apparatus is operating; a memory configured to store detected information; a physical controller configured to maintain a physical attribute of the autonomous actor apparatus, the physical attribute associated with a physical interaction of the apparatus with the environment; a behavior controller configured to maintain a behavior attribute of the autonomous actor apparatus; and a processor configured to: select a subset of the detected information based at least in part on a control sequence for the autonomous actor apparatus, wherein the control sequence includes a first portion controlling a physical attribute of the autonomous actor apparatus and a second portion of controlling a behavioral attribute of the autonomous actor apparatus; generate weighted measurements for the subset of the detected information, wherein a weight for a measurement is identified using the control sequence; create a first set of clusters representing individual weighted measurements, wherein clustering parameters for creating the first set of clusters are identified based at least in part on the control sequence; create a second set of clusters, each cluster representing composite measurements, wherein a composite measurement is generated using two or more weighted measurements from the first set of clusters, and wherein clustering parameters for the second set of clusters are identified based at least in part on the control sequence; create additional sets of clusters, each set representing a combination of elements from a previous set of clusters, wherein a number of additional sets is determined based on the control sequence, and wherein clustering parameters for each additional set of clusters are identified based at least in part on the control sequence; and adjust at least one of the behavior controller or the physical controller using at least one of: (i) the second set of clusters or (ii) at least one of the additional sets of clusters. ### Claim 2 (depends on 1) The autonomous actor apparatus of claim 1, wherein the processor is further configured to adjust the physical controller by: selecting a cluster included in one of the additional sets of clusters described based on the control sequence; altering the first portion of the control sequence using the cluster; and activating the physical controller using the altered control sequence. ### Claim 3 (depends on 1) The autonomous actor apparatus of claim 1, wherein the processor is further configured to adjust the physical controller by: identifying a desired final state; identifying first members of the first set of clusters that correspond with the desired final state; identifying second members of the second set of clusters that: (i) include composite measurements generated using the identified members of the first set of clusters and (ii) correspond with the desired final state; identifying additional members of an additional set of clusters that: (i) include composite measurements generated using the identified members of the second set of clusters and (ii) correspond with the desired final state; altering a portion of the control sequence including physical control parameters using the identified first members, second members, and additional members; and activating the physical controller using the altered control sequence. ### Claim 4 (depends on 1) The autonomous actor apparatus of claim 1, wherein the processor is further configured to: generate a plurality of vectors or matrices representing at least a portion of the weighted measurements, wherein a number of rows included in a matrix is determined based on a control sequence for the autonomous actor apparatus. ### Claim 5 (depends on 4) The autonomous actor apparatus of claim 4, wherein the processor is further configured to: generate a weight for each of the plurality of matrices using the control sequence for the autonomous actor apparatus, wherein creating a cluster comprises weighting values used to generate the cluster using the weights for each of the plurality of matrices. ### Claim 6 (depends on 4) The autonomous actor apparatus of claim 4, wherein the processor is further configured to: generate a current event matrix using detected information detected by the sensor after the plurality of matrices are generated; and compare the current event matrix with the plurality of matrices using the control sequence to identify a matrix included in the plurality of matrices corresponding to the current event matrix, wherein the processor adjusts at least one of the behavior controller or the physical controller based at least in part on the matrix included in the plurality of matrices corresponding to the current event matrix. ### Claim 7 (depends on 4) The autonomous actor apparatus of claim 4, wherein the processor is further configured to receive information about a second autonomous actor apparatus and an environment in which the second autonomous actor apparatus is operating, wherein the subset of information is further selected from the information received from the second autonomous actor apparatus based at least in part on the control sequence. ### Claim 8 (depends on 1) The autonomous actor apparatus of claim 1, wherein the detected information includes at least one of structured or unstructured data. ### Claim 9 (depends on 8) The autonomous actor apparatus of claim 8, wherein the structured data comprises clusters or hierarchies of data. ### Claim 10 (depends on 1) The autonomous actor apparatus of claim 1, wherein the physical controller comprises at least one of a wheel, an engine, a motor, a hydraulic cylinder, a pneumatic cylinder, a tread, a power source, a wing, a rotor, and a propeller; and wherein the sensor comprises at least one of a camera, a clock, an antenna, an accelerometer, a gravimeter, a radiometer, a barometer, a thermometer, a microphone, an infrared detector, a chemical sensor, a gyroscope, a photodetector, SONAR, and RADAR. ### Claim 11 A computer-implemented method of controlling an autonomous actor apparatus, the method comprising: under control of at least one computing device executing specific computer-executable instructions, receive information about the autonomous actor apparatus and an environment in which the autonomous actor apparatus is operating; select a subset of the information based at least in part on a control sequence for said autonomous actor apparatus; generate weighted measurements for the subset of the detected information, wherein a weight for a measurement is identified using the control sequence; create a first set of clusters representing individual weighted measurements, wherein clustering parameters for creating the first set of clusters are identified based at least in part on the control sequence; create a second set of clusters, each cluster representing composite measurements, wherein a composite measurement is generated using two or more weighted measurements from the first set of clusters, and wherein clustering parameters for the second set of clusters are identified based at least in part on the control sequence; create additional sets of clusters, each set representing a combination of elements from a previous set of clusters, wherein a number of additional sets is determined based on the control sequence, and wherein clustering parameters for each additional set of clusters are identified based at least in part on the control sequence; and adjust at least one of a behavior controller or a physical controller included in the autonomous actor apparatus using at least one of: (i) the second set of clusters or (ii) at least one of the additional sets of clusters. ### Claim 12 (depends on 11) The computer-implemented method of claim 11, wherein adjusting the physical controller comprises: selecting a cluster included in one of the additional sets of clusters described based on the control sequence; altering a portion of the control sequence including physical control parameters using the cluster; and activating the physical controller using the altered control sequence. ### Claim 13 (depends on 11) The computer-implemented method of claim 11, wherein adjusting the physical controller comprises: identifying a desired final state; identifying first members of the first set of clusters that correspond with the desired final state; identifying second members of the second set of clusters that: (i) include composite measurements generated using the identified members of the first set of clusters and (ii) correspond with the desired final state; identifying additional members of an additional set of clusters that: (i) include composite measurements generated using the identified members of the second set of clusters and (ii) correspond with the desired final state; altering a portion of the control sequence including physical control parameters using the identified first members, second members, and additional members; and activating the physical controller using the altered control sequence. ### Claim 14 (depends on 11) The computer-implemented method of claim 11, further comprising: generating a plurality of vectors or matrices representing at least a portion of the weighted measurements, wherein a number of rows included in a matrix is determined based on a control sequence for the autonomous actor apparatus. ### Claim 15 (depends on 14) The computer-implemented method of claim 14, further comprising: generating a weight for each of the plurality of matrices using the control sequence for the autonomous actor apparatus, wherein creating a cluster comprises weighting values used to generate the cluster using the weights for each of the plurality of matrices. ### Claim 16 (depends on 14) The computer-implemented method of claim 14, further comprising: generating a current event matrix using detected information detected by the sensor after the plurality of matrices are generated; and comparing the current event matrix with the plurality of matrices using the control sequence to identify a matrix included in the plurality of matrices corresponding to the current event matrix, wherein adjusting at least one of the behavior controller or the physical controller is based at least in part on the matrix included in the plurality of matrices corresponding to the current event matrix. ### Claim 17 (depends on 12) The computer-implemented method of claim 12, wherein altering the control sequence comprises at least one of: (i) changing a value included in the control sequence and (ii) removing a value included in the control sequence. ### Claim 18 (depends on 11) The computer-implemented method of claim 11, further comprising receiving information about a second autonomous actor apparatus and an environment in which the second autonomous actor apparatus is operating, wherein the subset of information is further selected from the information received from the second autonomous actor apparatus based at least in part on the control sequence. ### Claim 19 (depends on 18) The computer-implemented method of claim 18, wherein the control sequence includes a portion identifying which autonomous actors to select information from and a quantity of information to select from the identified autonomous actors, wherein the second autonomous actor is identified base at least in part on the portion of the control sequence. ### Claim 20 (depends on 11) The computer-implemented method of claim 11, wherein adjusting the physical controller comprises adjusting at least one of: a height, a width, a weight, a total surface area, a speed, an armor thickness, an engine output, a battery life, color, and a property indicating how the autonomous actor apparatus interacts with the environment.