MUMBAI, India, July 30 -- Intellectual Property India has published a patent application (202611052990 A) filed by Dr. K A Ajmath; Dr. Sakshi Sharma; Mr. Shivaji Rajaram Vasekar; Dr. P. Felcy Judith; Dr. Priyanka Halle; Srisailanath; Mrs. Veena Kiragi; Poonam C Fafat; Priyadharshini. Sp; Dr. Abhilash Pati; Dr. Amrutanshu Panigrahi; and Dr. Bibhuprasad Sahu on April 25, 2026, for An Autonomous Agent-Based Artificial Intelligence Framework For Goal-Driven Decision Making And Task Execution.
Inventors include Dr. K A Ajmath; Dr. Sakshi Sharma; Mr. Shivaji Rajaram Vasekar; Dr. P. Felcy Judith; Dr. Priyanka Halle; Srisailanath; Mrs. Veena Kiragi; Poonam C Fafat; Priyadharshini. Sp; Dr. Abhilash Pati; Dr. Amrutanshu Panigrahi; and Dr. Bibhuprasad Sahu.
The application for the patent was published on July 24, 2026, under issue no. 30/2026.
Abstract: The present invention discloses an autonomous agent-based artificial intelligence framework designed for goal-driven decision making and adaptive task execution in dynamic and complex environments. The framework introduces a distributed architecture composed of multiple intelligent agents capable of perceiving environmental conditions, analyzing contextual information, and making independent yet coordinated decisions. Each agent is equipped with perception, reasoning, learning, and action modules that enable continuous interaction with the environment and support intelligent behavior.A central goal management unit is incorporated to define, prioritize, and dynamically update system objectives based on changing conditions and system requirements. This ensures alignment between individual agent actions and overall system goals. The framework further includes a task management and scheduling module that dynamically allocates tasks to agents based on capability, availability, and priority, enabling efficient and flexible task execution. The invention integrates advanced learning techniques, including machine learning and reinforcement learning, allowing agents to learn from past experiences and improve decision-making over time. A communication and coordination module facilitates seamless interaction among agents, enabling collaboration, negotiation, and conflict resolution in distributed environments. Additionally, a monitoring and analytics module continuously tracks system performance, logs activities, and detects anomalies, ensuring transparency, reliability, and system optimization. The proposed framework minimizes human intervention while maintaining adaptability and scalability across various application domains such as robotics, enterprise automation, and Internet of Things environments. Overall, the invention provides a comprehensive and intelligent solution for autonomous decision making and task execution, significantly enhancing system efficiency, flexibility, and performance in real-world applications.
Disclaimer: Curated by HT Syndication.
