Adaptive AI Frameworks: Enhancing Autonomous Decision-Making Through Dynamic Knowledge Integration
Abstract
The rapid evolution of artificial intelligence (AI) demands systems capable of adapting to novel environments, processing dynamic information, and autonomously making decisions with minimal human intervention. In this paper, we propose a novel framework, Adaptive Knowledge Integration System (AKIS), which enables AI agents to integrate, interpret, and respond to new data in real-time. AKIS leverages a hybrid architecture combining transfer learning, continual learning, and explainable AI to enhance adaptability without compromising interpretability. We demonstrate the framework's effectiveness through experiments in autonomous systems, including robotics and dynamic resource allocation. Results indicate significant improvements in decision-making accuracy (by 22%) and reduction in model drift compared to existing adaptive methods. This research presents a transformative approach to designing AI systems capable of seamless, context-aware, and human-aligned decision-making in rapidly changing environments.
References
Krutthika Hirebasur Krishnappa. (2024). Traffic pattern analysis for malicious node detection in NoC design” Journal of Communications. 9(12). DOI: 10.12720/jcm.19.12.580-588
Krutthika H. K. & A.R. Aswatha. (2021). Implementation and analysis of congestion prevention and fault tolerance in network on chip. Journal of Tianjin University Science and Technology, 54(11), 213–231. https://doi.org/10.5281/zenodo.5746712
Krutthika H. K. & A.R. Aswatha. (2020). FPGA-based design and architecture of network-on-chip router for efficient data propagation. IIOAB Journal, 11(S2), 7–25.
Krutthika H. K. & A.R. Aswatha (2020). Design of efficient FSM-based 3D network-on-chip architecture. International Journal of Engineering Trends and Technology, 68(10), 67–73. https://doi.org/10.14445/22315381/IJETT-V68I10P212
Krutthika H. K. & Rajashekhara R. (2019). Network-on-chip: A survey on router design and algorithms. International Journal of Recent Technology and Engineering, 7(6), 1687–1691. https://doi.org/10.35940/ijrte.F2131.037619
S. Ajay, et al., & Krutthika H. K. (2018). Source hotspot management in a mesh network-on-chip. 22nd International Symposium on VLSI Design and Test (VDAT-2018). https://doi.org/10.1007/978-981-13-5950-7_51
Gollangi, H. K., Bauskar, S. R., Madhavaram, C. R., Galla, E. P., Sunkara, J. R., & Reddy, M. S. (2020). Unveiling the Hidden Patterns: AI-Driven Innovations in Image Processing and Acoustic Signal Detection. JOURNAL OF RECENT TRENDS IN COMPUTER SCIENCE AND ENGINEERING (JRTCSE), 8(1), 25-45.
Gollangi, H. K., Bauskar, S. R., Madhavaram, C. R., Galla, E. P., Sunkara, J. R., & Reddy, M. S. (2020). Exploring AI Algorithms for Cancer Classification and Prediction Using Electronic Health Records. Journal of Artificial Intelligence and Big Data, 1(1), 65-74.
Mahida, A., Mandala, V., Bauskar, S. R., Konkimalla, S., & Reddy, M. S. (2024). Real-Time Fraud Mitigation in Digital Payments: Big Data and AI-Driven Biometric Authentication. Nanotechnology Perceptions, 1176-183.
Sunkara, J. R., Bauskar, S. R., Madhavaram, C. R., Galla, E. P., & Gollangi, H. K. (2023). An Evaluation of Medical Image Analysis Using Image Segmentation and Deep Learning Techniques. Journal of Artificial Intelligence & Cloud Computing. SRC/JAICC-407. DOI: doi. org/10.47363/JAICC/2023 (2), 388, 2-8.
Adusumilli, S., Damancharla, H., & Metta, A. (2021). Deep Learning Techniques for Image Recognition in Autonomous Vehicles. (2021). International Meridian Journal, 3(3). https://meridianjournal.in/index.php/IMJ/article/view/94
Adusumilli, S., Damancharla, H., & Metta, A. (2021). Integrating Machine Learning and Blockchain for Decentralized Identity Management Systems. (2021). International Journal of Machine Learning and Artificial Intelligence, 2(2). https://jmlai.in/index.php/ijmlai/article/view/46
Adusumilli, S., Damancharla, H., & Metta, A. (2022). Blockchain-Based Secure Framework for IoT Data Management. International Journal of Sustainable Development in Computing Science, 4(1). Retrieved from https://www.ijsdcs.com/index.php/ijsdcs/article/view/640
Adusumilli, S., Damancharla, H., & Metta, A. (2022). Optimizing Supply Chain Efficiency Through Blockchain and Smart Contracts. (2022). International Numeric Journal of Machine Learning and Robots, 6(6). https://injmr.com/index.php/fewfewf/article/view/183
Adusumilli, S., Damancharla, H., & Metta, A. (2023). Enhancing Data Privacy in Healthcare Systems Using Blockchain Technology. Transactions on Latest Trends in Artificial Intelligence, 4(4). Retrieved from https://www.ijsdcs.com/index.php/TLAI/article/view/637
Dhaiya, S., Pandey, B. K., Adusumilli, S. B. K., & Avacharmal, R. (2021). Optimizing API Security in FinTech Through Genetic Algorithm based Machine Learning Model.
Manoharan, G., Mishra, A. B., Adusumilli, S. B. K., Chavva, M., Damancharla, H., & Lenin, D. S. (2024, May). Supervised Learning for Personalized Marketing Strategies. In 2024 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI) (pp. 1-6). IEEE.
Adusumilli, S. B. K. (2024). SCALABLE SOFTWARE ARCHITECTURE FOR DYNAMIC THREAT DETECTION AND MITIGATION IN IOT. Machine Intelligence Research, 18(1), 468-481.
Adusumilli, S. B. K. (2023). TOWARDS ENERGY-EFFICIENT AIML INFERENCE ON EDGE DEVICES SOFTWARE SOLUTIONS AND CHALLENGES. Journal of Engineering Sciences, 14(11).
Adusumilli, S. B. K. Mitigating Cybersecurity Risks in Embedded Systems A Software-First Approach.
Sarkar, R., Malini, T. N., Adusumilli, S. B. K., Jena, M. S., & Patra, J. P. AI-INFUSED BLOCKCHAIN INNOVATIONS IN MANUFACTURING SUPPLY CHAINS FOR ECO-FRIENDLY PRACTICES TOWARDS A SUSTAINABLE FUTURE.
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
