Abstract: Dynamic calibration of cameras in a stereoscopic configuration may include: determining a disparity between first image data from a first camera and second image data from a second camera, wherein the first camera and the second camera are in a stereoscopic configuration, and wherein the disparity comprises a difference in placement of one or more objects in the first image data relative to the second image data; and adjusting one or more of the first camera or the second camera, based on the disparity and sensor data from a sensor other than the first camera and the second camera, to calibrate the stereoscopic configuration of the first camera and the second camera to achieve stereoscopic camera distance functionality.

Abstract: A data processing system for providing a black-box optimization exchange implements receiving a black-box optimization problem, presenting the problem on a user interface, receiving a candidate solution, inserting the candidate solution into a candidate solution queue, providing the candidate solution to a simulator service cause the simulator service to execute an objective function associated with the black-box optimization problem on the candidate solution, determining an improvement value provided by the candidate solution by analyzing one or more previously determined solutions to the first black-box optimization problem and the first objective value to determine an amount of improvement provided by the candidate solution, determining a reward by analyzing the improvement value using a reward function associated with the black-box optimization problem, and notifying the user that provided the candidate solution that the candidate solution has earned the user the reward.

Abstract: A data processing system for providing a black-box optimization exchange implements receiving a black-box optimization problem, presenting the problem on a user interface, receiving a candidate solution, inserting the candidate solution into a candidate solution queue, providing the candidate solution to a simulator service cause the simulator service to execute an objective function associated with the black-box optimization problem on the candidate solution, determining an improvement value provided by the candidate solution by analyzing one or more previously determined solutions to the first black-box optimization problem and the first objective value to determine an amount of improvement provided by the candidate solution, determining a reward by analyzing the improvement value using a reward function associated with the black-box optimization problem, and notifying the user that provided the candidate solution that the candidate solution has earned the user the reward.

Abstract: A data processing system for providing a black-box optimization exchange implements receiving a black-box optimization problem, presenting the problem on a user interface, receiving a candidate solution, inserting the candidate solution into a candidate solution queue, providing the candidate solution to a simulator service cause the simulator service to execute an objective function associated with the black-box optimization problem on the candidate solution, determining an improvement value provided by the candidate solution by analyzing one or more previously determined solutions to the first black-box optimization problem and the first objective value to determine an amount of improvement provided by the candidate solution, determining a reward by analyzing the improvement value using a reward function associated with the black-box optimization problem, and notifying the user that provided the candidate solution that the candidate solution has earned the user the reward.

Abstract: A data processing system for providing a black-box optimization exchange implements receiving a black-box optimization problem, presenting the problem on a user interface, receiving a candidate solution, inserting the candidate solution into a candidate solution queue, providing the candidate solution to a simulator service cause the simulator service to execute an objective function associated with the black-box optimization problem on the candidate solution, determining an improvement value provided by the candidate solution by analyzing one or more previously determined solutions to the first black-box optimization problem and the first objective value to determine an amount of improvement provided by the candidate solution, determining a reward by analyzing the improvement value using a reward function associated with the black-box optimization problem, and notifying the user that provided the candidate solution that the candidate solution has earned the user the reward.