MUMBAI, India, July 13 -- Intellectual Property India has published a patent application (202641082494 A) filed by Dr V. Balajishanmugam; Dr. A. Suganya; Chandrika G; Sangeetha K; Dr. B. Dhanalakshmi; and T. Glen Sudarson on July 03, 2026, for System And Method For Strategic Gameplay Optimization Using Reinforcement Learning Framework.
Inventors include Dr V. Balajishanmugam; Dr. A. Suganya; Chandrika G; Sangeetha K; Dr. B. Dhanalakshmi; and T. Glen Sudarson.
The application for the patent was published on July 10, 2026, under issue no. 28/2026.
Abstract: ABSTRACT SYSTEM AND METHOD FOR STRATEGIC GAMEPLAY OPTIMIZATION USING REINFORCEMENT LEARNING FRAMEWORK The invention discloses a modular reinforcement learning system for strategic gameplay optimization. The system comprises a state observation unit, a policy generation engine, a reward evaluation module, and a feedback loop controller. Together, these modules enable autonomous agents to dynamically adapt strategies, anticipate opponent behavior, and optimize decision-making in complex game environments. The state observation unit captures environmental inputs, while the policy generation engine derives optimal strategies using reinforcement learning algorithms with modular traceability. The reward evaluation module incorporates predictive intelligence to assess immediate and long-term outcomes across multiple zones of gameplay. The feedback loop controller enables continuous learning and rapid adaptation without exhaustive retraining, thereby improving efficiency and scalability. The modular architecture supports compliance-driven documentation, traceability, and integration with external platforms. By combining modular design, predictive intelligence, and adaptive feedback loops, the invention addresses limitations of prior art and provides a scalable, transparent, and efficient solution for reinforcement learning applications in strategic gameplay.
Disclaimer: Curated by HT Syndication.
