The Cognitive Engine employs a self-hyperparameter tuning subcomponent to iteratively optimize complex black-box functions in a decentralized manner. In ACES, this enables the efficient configuration of swarming algorithms, with Python-based software that includes application examples for benchmark problem-solving, Model Predictive Controller (MPC) tuning for autonomous driving, and hyperparameter optimization for swarm intelligence benchmarks. The SUPSI’s focus on the ACES project is to implement the earlier mentioned Swarm Hyperparameter Tuning Model that is being the part of the Swarm Intelligent Orchestrator itself, which is a component implemented by Lake. For now, this component is on verge of integration with another component provided by HIRO – Cognitive Framework.