METHOD FOR DESIGNING GENETIC CODE FOR SOFTWARE ROBOT

• US 20090024249A1
• Filed: 07/16/2008
• Published: 01/22/2009
• Est. Priority Date: 07/16/2007
• Status: Abandoned Application

• Current Assignee: Samsung Electronics Co. Ltd.
• Original Assignee: Samsung Electronics Co. Ltd.
• Inventors: Choi, Seung-Hwan, Kim, Kwang-Choon, Kim, Jong-Hwan, Lee, Kang-Hee
• Application Number:
  US12/173,905
• Publication Number:
  US 20090024249A1
• Time in Patent Office: Days
• US Class Current: 700/245
• CPC Class Codes: G06N 3/006 based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO]
• CPC Class Codes: G06N 3/126 Evolutionary algorithms, e.g. genetic algorithms or genetic programming

Abstract

A method for designing a genetic code for a software robot in a software robot apparatus is provided in which a request for writing a genetic code for a software robot is received from a user, a plurality of intuition traits associated with one or more pieces of genetic information among genetic information included in the genetic code are provided, a value of an intuition trait selected from among the plurality of intuition traits is changed according to a user input, a representation value of each piece of genetic information related to the selected intuition trait is changed by applying the changed value of the intuition trait to a predetermined conversion formula, and the software robot is implemented according to representation values of the genetic information included in the genetic code, an external stimulus, and an internal state change of the software robot.

Claims

1. A method for operating an artificial creature having a unique genetic code and capable of moving, the genetic code including at least one piece of genetic information, the method comprising:

receiving an intuition trait value associated with at least one piece of genetic information among pieces of genetic information included in the genetic code from a user;

updating an existing intuition trait with the received intuition trait value;

changing a representation value of the associated at least one piece of genetic information based on the updated intuition trait; and

operating the artificial creature according to the changed representation value.

2. The method of claim 1, wherein the genetic information includes at least one of an inner state representation value, an external stimulus representation value, and behavior determining genetic information.

3. The method of claim 1, wherein the intuition trait value represents one of a plurality of perceptive and emotional traits.

4. The method of claim 1, wherein the genetic information changes according to one of an inner state change and an external state change and is a unique value to the artificial creature, determined by a user input.

5. The method of claim 1, wherein the artificial creature is one of a genetic robot and a software robot.

6. A method for designing a genetic code for a software robot in a software robot apparatus, comprising;

receiving a request for writing a genetic code for a software robot from a user;

providing a plurality of intuition traits associated with at least one piece of genetic information included in the genetic code;

changing a value of an intuition trait selected from among the plurality of intuition traits according to a user input;

changing a representation value of each piece of genetic information related to the selected intuition trait by applying the changed value of the intuition trait to a predetermined conversion formula; and

implementing the software robot according to representation values of the at least one piece of genetic information included in the genetic code, an external stimulus, and an internal state change of the software robot.

7. The method of claim 6, further comprising, upon receipt from the user of a request for changing a representation value of a certain genetic information, changing the representation value of the certain piece of genetic information and changing a value of an intuition trait related to the certain piece of genetic information according to a predetermined conversion formula.

8. The method of claim 7, further comprising, after changing the representation value of the certainpiece of genetic information, changing values of a pair of homologous chromosomes constituting the certain piece of genetic information based on the change representation value according to a predetermined inheritance law.

9. The method of claim 8, wherein the inheritance law is an application of a biological inheritance law.

10. The method of claim 8, wherein the inheritance law is set by applying one of the laws selected from the group consisting of Mendelian genetics, law of intermediate inheritance, law of independence assortment, law of segregation, and law of dominance.

19. The method of claim 6, wherein the genetic code includes at least one personality gene related to at least one internal state of the software robot and at least one outward gene related to an outer appearance of the software robot.

11. A method for designing a genetic code for a software robot in a software robot apparatus, comprising;

setting genetic code of at least one software robot as a genetic code of each of a pair of parent software robots; and

creating new genetic information by combining paired homologous chromosomes of genetic information counterparts included in genetic information provided by the genetic code of each of the pair of the parent software robots, according to a predetermined gene crossover rule.

12. The method of claim 11, further comprising:

completely designing a new genetic code by converting values of a pair of homologous chromosomes constituting each piece of the created new genetic information to a representation value of each piece of genetic information according to a predetermined inheritance law; and

creating a child software robot according to representation values of genetic information included in the new genetic code.

13. The method of claim 12, wherein two different software robots are set as the pair of parent software robots.

14. The method of claim 12, wherein the genetic code setting comprises setting a genetic code of a single software robot as the genetic code of each of the pair of parent software robots.

15. The method of claim 12, wherein the inheritance law is an application of a biological inheritance law.

16. The method of claim 15, wherein the inheritance law is set by applying one of laws selected from the group consisting of Mendelian genetics, law of intermediate inheritance, law of independence assortment, law of segregation, and law of dominance.

17. The method of claim 12, wherein the gene crossover rule is a rule that randomly combines paired homologous chromosomes constituting genetic information counterparts in each of the pair of parent software robots.

18. The method of claim 12, wherein the genetic code setting comprises:

sensing whether at least two different software robots are located within a crossover available distance;

setting, if it is sensed that two different software robots are located within the crossover available distance, genetic codes of the two software robots as the genetic codes of the pair of parent software robots;

setting, if it is sensed that three different software robots are located within the crossover available distance, genetic codes of two closest software robots as the genetic codes of the pair of parent software robots; and

setting, if it is sensed that at least four different software robots are located within the crossover available distance, genetic codes of software robots selected by a user as the genetic codes of the pair of parent software robots.

20. The method of claim 11, wherein each of the genetic codes includes at least one personality gene related to at least one internal state of a software robot and at least one outward gene related to an outer appearance of the software robot.