US 12,222,849 B2
Infrastructure refactoring via fuzzy upside down reinforcement learning
Madhu Sudhanan Krishnamoorthy, Tamil Nadu (IN); Sreeram Raghavan, Tamil Nadu (IN); and Rajarajan Pandiyan, Chennai (IN)
Assigned to Bank of America Corporation, Charlotte, NC (US)
Filed by Bank of America Corporation, Charlotte, NC (US)
Filed on May 3, 2021, as Appl. No. 17/246,801.
Prior Publication US 2022/0350732 A1, Nov. 3, 2022
Int. Cl. G06N 20/00 (2019.01); G06F 11/34 (2006.01); G06F 11/36 (2006.01); G06F 16/23 (2019.01); G06N 5/02 (2023.01); G06N 5/048 (2023.01)
CPC G06F 11/3688 (2013.01) [G06F 11/3457 (2013.01); G06F 11/3616 (2013.01); G06F 11/3664 (2013.01); G06F 16/2379 (2019.01); G06N 5/02 (2013.01); G06N 20/00 (2019.01); G06N 5/048 (2013.01)] 21 Claims
OG exemplary drawing
 
1. A method for improving application throughput by refactoring infrastructure, the method comprising:
(a) defining a set of parameters of an application landscape;
(b) stress-testing an application in a simulated environment based on:
the parameters; and
a simulated input to the application;
the stress-testing comprising (1) generating a simulated hardware environment, (2) instantiating the application in the simulated hardware environment, (3) porting in the application landscape parameters, and (4) detecting an output comprising an application throughput;
(c) identifying an initial state of stress of the application based on output of the stress-test;
(d) generating an updated state of stress based on linear combinations of fuzzified basis vectors based on the initial state of stress, the fuzzified basis vectors based on the application landscape parameters;
(e) repeating, sequentially, (b) and (d), with a new application parameter in the set of parameters, and the initial state of stress replaced by the latest updated state of stress, until the updated state of stress satisfies a predetermined stochastic threshold;
(f) providing the updated state of stress to an upside down reinforcement learning (“UDRL”) engine;
(g) comparing a throughput corresponding to the updated state of stress to a benchmark throughput;
(h) re-weighting the parameters; and
(i) repeating (a)-(i) until a threshold proximity to the benchmark throughput is reached and outputting a set of parameters and weights associated with the benchmark throughput.