US 12,417,464 B2
Autonomous contingency-responsive smart contract configuration system
Charles Howard Cella, Pembroke, MA (US); and Andrew S. Locke, Farmington, MI (US)
Assigned to STRONG FORCE VCN PORTFOLIO 2019, LLC, Fort Lauderdale, FL (US)
Filed by Strong Force VCN Portfolio 2019, LLC, Fort Lauderdale, FL (US)
Filed on Mar. 7, 2023, as Appl. No. 18/179,960.
Application 18/179,960 is a continuation in part of application No. PCT/US2022/028633, filed on May 10, 2022.
Application 18/179,960 is a continuation in part of application No. PCT/US2022/025103, filed on Apr. 15, 2022.
Claims priority of provisional application 63/302,013, filed on Jan. 21, 2022.
Claims priority of provisional application 63/299,710, filed on Jan. 14, 2022.
Claims priority of provisional application 63/282,507, filed on Nov. 23, 2021.
Claims priority of provisional application 63/187,325, filed on May 11, 2021.
Claims priority of provisional application 63/176,198, filed on Apr. 16, 2021.
Claims priority of application No. 202211008709 (IN), filed on Feb. 18, 2022.
Prior Publication US 2023/0222531 A1, Jul. 13, 2023
Int. Cl. G06Q 10/00 (2023.01); G05B 13/00 (2006.01); G05B 13/04 (2006.01); G06F 9/00 (2006.01); G06F 9/48 (2006.01); G06N 5/00 (2023.01); G06N 5/043 (2023.01); G06N 10/00 (2022.01); G06N 10/60 (2022.01); G06N 10/80 (2022.01); G06N 20/00 (2019.01); G06Q 10/0631 (2023.01); G06Q 10/087 (2023.01); G06Q 30/00 (2023.01); G06Q 30/0201 (2023.01); G06Q 30/0601 (2023.01); G06Q 40/00 (2023.01); G06Q 40/04 (2012.01)
CPC G06Q 30/0206 (2013.01) [G05B 13/048 (2013.01); G06F 9/4881 (2013.01); G06N 5/043 (2013.01); G06N 10/60 (2022.01); G06N 10/80 (2022.01); G06N 20/00 (2019.01); G06Q 10/0631 (2013.01); G06Q 10/06315 (2013.01); G06Q 10/087 (2013.01); G06Q 30/0201 (2013.01); G06Q 30/0625 (2013.01); G06Q 40/04 (2013.01)] 18 Claims
OG exemplary drawing
 
1. A system for managing a set of future costs associated with a product, the system comprising:
a future requirement system programmed to estimate an amount of resources required for manufacturing, distributing, and selling the product at a future point in time;
an adverse contingency system configured to identify a set of adverse contingencies and calculate changes in a set of costs associated with obtaining the amount of resources at the future point in time; and
a smart contract system configured to autonomously configure and execute a smart futures contract based on the amount of resources required and on the changes in the set of costs to manage the set of future costs associated with the product, wherein:
the smart contract system is configured to configure the smart futures contract by using a machine learning robotic agent to autonomously determine terms and conditions for the smart futures contract,
the smart contract system is configured to train the machine learning robotic agent on a training set of data,
the training set of data is based on a training set of interactions of a set of users with a set of inputs, and
the smart contract system is configured to retrain the machine learning robotic agent based on feedback from a set of outcomes of the set of adverse contingencies.