	US 12,204,921 B2
	System and methods for creation and use of meta-models in simulated environments
Jason Crabtree, Vienna, VA (US); and Andrew Sellers, Monument, CO (US)
Assigned to QOMPLX LLC, Reston, VA (US)
Filed by QOMPLX LLC, Reston, VA (US)
Filed on Jun. 23, 2021, as Appl. No. 17/355,499.
Application 17/355,499 is a continuation in part of application No. 15/882,180, filed on Jan. 29, 2018, granted, now 11,055,601.
Application 15/882,180 is a continuation in part of application No. 15/835,436, filed on Dec. 7, 2017, granted, now 10,572,828, issued on Feb. 25, 2020.
Application 15/835,436 is a continuation in part of application No. 15/790,457, filed on Oct. 23, 2017, granted, now 10,884,999.
Application 15/790,457 is a continuation in part of application No. 15/790,327, filed on Oct. 23, 2017, granted, now 10,860,951.
Application 15/790,457 is a continuation in part of application No. 15/616,427, filed on Jun. 7, 2017, abandoned.
Application 15/790,327 is a continuation in part of application No. 14/925,974, filed on Oct. 28, 2015, abandoned.
Application 15/790,327 is a continuation in part of application No. 15/141,752, filed on Apr. 28, 2016, granted, now 10,860,962.
Application 15/141,752 is a continuation in part of application No. 15/091,563, filed on Apr. 5, 2016, granted, now 10,204,147, issued on Feb. 12, 2019.
Application 15/141,752 is a continuation in part of application No. 14/986,536, filed on Dec. 31, 2015, granted, now 10,210,255, issued on Feb. 19, 2019.
Application 15/141,752 is a continuation in part of application No. 14/925,974, filed on Oct. 28, 2015, abandoned.
Application 15/882,180 is a continuation in part of application No. 15/835,312, filed on Dec. 7, 2017, granted, now 11,055,451.
Application 15/835,312 is a continuation in part of application No. 15/186,453, filed on Jun. 18, 2016, abandoned.
Application 15/186,453 is a continuation in part of application No. 15/166,158, filed on May 26, 2016, abandoned.
Application 15/166,158 is a continuation in part of application No. 15/141,752, filed on Apr. 28, 2016, granted, now 10,860,962.
Claims priority of provisional application 62/568,291, filed on Oct. 4, 2017.
Claims priority of provisional application 62/568,298, filed on Oct. 4, 2017.
Prior Publication US 2022/0019451 A1, Jan. 20, 2022
This patent is subject to a terminal disclaimer.
Int. Cl. G06F 9/455 (2018.01); G06F 8/30 (2018.01); G06F 8/41 (2018.01); G06F 30/27 (2020.01); H04L 41/0813 (2022.01); G06Q 10/067 (2023.01)

CPC G06F 9/455 (2013.01) [G06F 8/30 (2013.01); G06F 8/41 (2013.01); G06F 30/27 (2020.01); H04L 41/0813 (2013.01); G06Q 10/067 (2013.01)]

4 Claims

1. A system for generating meta-models in simulated environments, comprising:

a computing device comprising a memory and a processor;

a meta-model module comprising a first plurality of programming instructions stored in the memory and operating on the processor, wherein the first plurality of programming instructions, when operating on the processor, cause the computing device to:

obtain one or more models of an agent; generate source code of the one or more models of an agent;

compile the source code to provide compiled code; and

reconfigure two or more compiled codes from at least two agents to provide a meta-model relating to a plurality of interactions between the at least two agents; and

at least one simulation manager comprising a second plurality of programming instructions stored in the memory and operating on the processor, wherein the second plurality of programming instructions, when operating on the processor, cause the computing device to:

receive a simulation goal related to one or more agent goals;

select a dynamic environment simulation based on the simulation goal;

execute the dynamic environment simulation using a plurality of meta-models; and

continue the execution of the dynamic environment simulation that evolves with agent behavior from the execution of the plurality of agents and the plurality of meta-models until the simulation goal has been reached or until each agent has achieved its agent goal from the one or more agent goals; and

an agent creation engine comprising a third plurality of programming instructions stored in the memory and operating on the processor, wherein the third plurality of programming instructions, when operating on the processor, cause the computing device to

create a plurality of agents, wherein each agent is an individual instance based on the one or more models of an agent;

assign at least one agent goal to each created agent; and

provide the created agents for use in the execution of the dynamic environment simulation;

wherein each of the plurality of agents takes different actions in a non-deterministic environment based on its specifications and the specifications of the dynamic environment simulation to achieve the one or more agent goals;

wherein the different actions and learned behaviors acquired by individual agents further differentiating them from each other during the simulation execution.