array

Array framework employs temperature reasoning to control creativity and randomness in sub-agents' decision-making processes. By tuning the temperature parameter, the framework strikes a balance between exploration (creative problem-solving) and exploitation (focused precision). This adaptability allows sub-agents to effectively tackle tasks of varying complexity and uncertainty.

The rapid progress in AI has sparked interest in hybrid models that integrate classical and quantum computing. Array represents a proof-of-concept swarm framework, demonstrating how quantum principles and collaborative distributed agents can enhance traditional AI capabilities. In this framework, individual agents operate autonomously, generating partial solutions to complex problems. These solutions are then combined during a collective reasoning phase to produce cohesive and optimized results.