Abstract: A genetic algorithm system generates a set of computer programs and executes a process for assessment and conditional modification of the set, repeating the process over a plurality of generations to mutate the population of solutions over time. At each generation, the system scores each program in the set to generate a respective primary score adjustment, a respective secondary score adjustment, and a respective current score. If a current score for a program is less than or equal to a first threshold, the system removes the computer program from the set. If the current score is greater than or equal to a second threshold, the system modifies the computer program to generate one or more offspring programs for use in subsequent generations. If a primary score adjustment for a program is greater than or equal to a third threshold, the system selects the computer program for performance of a task.

Abstract: A genetic algorithm system generates a set of computer programs and executes a process for assessment and conditional modification of the set, repeating the process over a plurality of generations to mutate the population of solutions over time. At each generation, the system scores each program in the set to generate a respective primary score adjustment, a respective secondary score adjustment, and a respective current score. If a current score for a program is less than or equal to a first threshold, the system removes the computer program from the set. If the current score is greater than or equal to a second threshold, the system modifies the computer program to generate one or more offspring programs for use in subsequent generations. If a primary score adjustment for a program is greater than or equal to a third threshold, the system selects the computer program for performance of a task.

Abstract: Disclosed herein are systems and methods for simulating an environment over a plurality of intervals of in-simulation time by using a two-part data structure to represent agents or entities in the simulation. A system may create and store a data structure representing an agent in the simulation, wherein a first portion of the data structure represents characteristics of the agent at a present interval and a second portion of data structure represents characteristics of the agent at a future interval of the simulation. Also disclosed herein are systems and methods for executing a multi-agent simulation using multiple processing threads. A system may group a plurality of agents in the simulated environment into subsets associated respectively with nodes of the simulated environment, assign the subsets to respective separate processors of the system, and execute the simulation using separate processing threads associated respectively with the separate processors.

Abstract: Disclosed herein are systems and methods for simulating an environment over a plurality of intervals of in-simulation time by using a two-part data structure to represent agents or entities in the simulation. A system may create and store a data structure representing an agent in the simulation, wherein a first portion of the data structure represents characteristics of the agent at a present interval and a second portion of data structure represents characteristics of the agent at a future interval of the simulation. Also disclosed herein are systems and methods for executing a multi-agent simulation using multiple processing threads. A system may group a plurality of agents in the simulated environment into subsets associated respectively with nodes of the simulated environment, assign the subsets to respective separate processors of the system, and execute the simulation using separate processing threads associated respectively with the separate processors.

Abstract: Disclosed herein are systems and methods for simulating an environment over a plurality of intervals of in-simulation time by using a two-part data structure to represent agents or entities in the simulation. A system may create and store a data structure representing an agent in the simulation, wherein a first portion of the data structure represents characteristics of the agent at a present interval and a second portion of data structure represents characteristics of the agent at a future interval of the simulation. Also disclosed herein are systems and methods for executing a multi-agent simulation using multiple processing threads. A system may group a plurality of agents in the simulated environment into subsets associated respectively with nodes of the simulated environment, assign the subsets to respective separate processors of the system, and execute the simulation using separate processing threads associated respectively with the separate processors.

Abstract: Disclosed herein are systems and methods for simulating an environment over a plurality of intervals of in-simulation time by using a two-part data structure to represent agents or entities in the simulation. A system may create and store a data structure representing an agent in the simulation, wherein a first portion of the data structure represents characteristics of the agent at a present interval and a second portion of data structure represents characteristics of the agent at a future interval of the simulation. Also disclosed herein are systems and methods for executing a multi-agent simulation using multiple processing threads. A system may group a plurality of agents in the simulated environment into subsets associated respectively with nodes of the simulated environment, assign the subsets to respective separate processors of the system, and execute the simulation using separate processing threads associated respectively with the separate processors.

Abstract: A mortgage loan pricing application that allows a mortgage professional to obtain loan pricing for a loan scenario from multiple lender prequalification systems in near real-time. The pricing application includes a loan pricing search engine that allows a mortgage professional to enter loan scenario information for the borrower. The loan pricing search engine contacts multiple lender prequalification systems and submits the loan scenario information to each of the prequalification systems. The loan pricing search engine presents the loan scenario information in the format required by the lender prequalification system. The loan pricing search engine receives loan pricing information from each lender, parses the quotes, and compiles the quotes to present the quotes in a compiled, normalized format.

Abstract: An energy management system for monitoring and analyzing the power consumption at a plurality of locations. The energy management system includes a primary server connected to at least one building server or other device through a computer network. Each of the building servers are connected to one or more energy meters contained in a building. The primary server sends out a data request and receives energy usage information from each of the individual building servers. The primary server stores the energy usage information in a power database such that the information can be processed in a variety of manners, such as aggregating the energy usage information from multiple locations into a single energy consumption statistic. The primary server can be accessed by remote monitoring stations to view and analyze the energy usage information stored in the power database.

Abstract: An energy management system for monitoring and analyzing the power consumption at a plurality of locations. The energy management system includes a primary server connected to at least one building server or other device through a computer network. Each of the building servers are connected to one or more energy meters contained in a building. The primary server sends out a data request and receives energy usage information from each of the individual building servers. The primary server stores the energy usage information in a power database such that the information can be processed in a variety of manners, such as aggregating the energy usage information from multiple locations into a single energy consumption statistic. The primary server can be accessed by remote monitoring stations to view and analyze the energy usage information stored in the power database.