Quantum Intelligent Agent of Medical Decision: The Theoretical Machine
Eustache Muteba A., Nikos E. Mastorakis
This paper presents the theoretical machine of a Quantum Intelligent Agents of Medical Decision. Introducing the concept of Intelligent Agents in Quantum Deep Q-Learning involves integrating principles of reinforcement learning, quantum computing, and intelligent agent frameworks. The theoretical machine is designed to simulate quantum computer and to explore quantum algorithms without the need for physical hardware (quantum computer). Our approach does not refer directly to any simulator. Oriented to the Sickle Cell Disease, the approach leverages quantum-inspired representations of classical Deep Reinforcement Learning to handle management of related medical data for an optimized treatment recommendations.
DESIGN CONSTRUCTION MAINTENANCE•Jul 9, 2025•0 citations