The latest articles on DEV Community by 24P-0578 Fatima Zoalfqar (@24p0578_fatimazoalfqar_). https://dev.to/24p0578_fatimazoalfqar_ https://media2.dev.to/dynamic/image/width=90,height=90,fit=cover,gravity=auto,format=auto/https:%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Fuser%2Fprofile_image%2F3822549%2Fd8939150-7ca6-4deb-b855-6b1e470c0940.png https://dev.to/24p0578_fatimazoalfqar_ en 24P-0578 Fatima Zoalfqar Fri, 13 Mar 2026 14:47:50 +0000 https://dev.to/24p0578_fatimazoalfqar_/understanding-modern-ai-adaptive-a-search-and-agentic-ai-2jd5 https://dev.to/24p0578_fatimazoalfqar_/understanding-modern-ai-adaptive-a-search-and-agentic-ai-2jd5 <p>Introduction:<br> Artificial Intelligence is developing very quickly. Researchers are constantly improving AI algorithms and systems. In our AI course we studied topics like search algorithms and intelligent agents.</p> <p>In this blog, I explored two research papers related to these topics. The first paper improves the A* search algorithm and the second paper explains the concept of Agentic AI.</p> <p>**</p> <h2> Paper 1: Adaptive A* Search Algorithm: </h2> <p>**</p> <p>The A* algorithm is one of the most common search algorithms used in artificial intelligence. It is used to find the best or shortest path between two points.</p> <p>The algorithm uses two values:<br> the actual cost from the start node and the estimated distance to the goal.</p> <p>Sometimes the algorithm explores many unnecessary paths which can make the search slower.</p> <p>The research paper “Research on the A Algorithm Based on Adaptive Weights (2025)”* improves the algorithm by introducing adaptive weights. This means the importance of the heuristic value can change during the search process.</p> <p>Because of this improvement, the algorithm can focus on better paths and reduce unnecessary exploration. This makes the search faster and more efficient.</p> <p>This research connects to the informed search algorithms we studied in our AI course.</p> <h2> <strong>Paper 2: The Rise of Agentic AI:</strong> </h2> <p>The second paper explains the idea of Agentic AI.</p> <p>Agentic AI systems are artificial intelligence systems that can act more independently. They can observe their environment, make decisions, and perform tasks to achieve goals.</p> <p>Traditional AI systems usually perform tasks when given instructions. However, agentic AI systems behave more like intelligent agents that can plan actions and solve problems on their own.</p> <p>The paper also discusses challenges such as safety, reliability, and controlling autonomous AI systems.</p> <p>This concept connects to the intelligent agents model we studied in class.</p> <h2> <strong>Personal Insights</strong> </h2> <p>While reading the papers and using NotebookLM, I understood the ideas more clearly. NotebookLM helped explain difficult parts of the research papers in simple language.</p> <p>One interesting thing I learned is that AI research is improving both search algorithms and intelligent agents. These improvements can help AI systems become faster and more independent.</p> <p>Video Explanation</p> <p>Here is my video explaining these papers:</p> <p><a href="https://youtu.be/SZIPveQmd9g" rel="noopener noreferrer">https://youtu.be/SZIPveQmd9g</a></p> <p>About Me</p> <p>Hello! I’m Fatima Zolfqar, a FAST University student interested in Artificial Intelligence.<br> <a class="mentioned-user" href="https://dev.to/raqeeb_26">@raqeeb_26</a></p> agents ai algorithms computerscience