Deep HJB Solver Skillv1.0.2

A quantitative finance firm needs to solve Hamilton-Jacobi-Bellman equations for optimal portfolio allocation under stochastic volatility. They require generating new training code for a 2D domain with two control variables representing stock and bond allocations, adapting sampling hyperparameters for better convergence, and creating analysis plots from CSV outputs to validate results.

An autonomous vehicle company needs to refactor existing HJB code for real-time optimal path planning with obstacle avoidance. They require adding a new problem configuration for 2D spatial domains representing vehicle position, implementing custom loss functions for collision constraints, and creating visualization code to analyze training performance across different scenarios.

A utility company needs to solve HJB equations for optimal power dispatch across a smart grid network. They require generating new problem code for a 1D domain representing time-varying demand, adapting training hyperparameters for faster convergence with limited computational resources, and creating plotting code to compare different control strategies from CSV training outputs.

A pharmaceutical research team needs to create HJB training code for optimal drug administration schedules that maximize therapeutic effect while minimizing side effects. They require implementing a new problem with terminal payoff functions representing patient outcomes, configuring appropriate sampling strategies for the 1D time domain, and generating analysis code to validate model predictions against clinical data.

A logistics company needs to refactor existing HJB solver code for optimal inventory management across multiple warehouses. They require adding new control variables for different product categories, implementing custom loss functions that incorporate storage costs and demand uncertainty, and creating visualization tools to analyze the training convergence across different parameter settings.

Offer specialized consulting to companies needing HJB solutions, providing custom code generation, hyperparameter tuning, and analysis visualization. Charge per project based on problem complexity and domain requirements, with ongoing support contracts for model maintenance and updates.

Develop a cloud-based platform where users can upload their HJB problem specifications and receive automatically generated training code, configuration files, and visualization outputs. Offer tiered subscriptions based on computational resources, problem complexity, and support levels.

Provide comprehensive training programs teaching engineers and researchers how to use the DGM framework for HJB problems. Offer certification programs, workshops, and custom corporate training sessions focused on specific industry applications like finance or autonomous systems.