[0:06]Hello everyone, welcome to this video on uninformed versus informed search in artificial intelligence by Simplylearn. And let me tell you guys that we have regular updates on multiple technologies. If you are a tech geek on a continuous hunt for the latest technological trends, then consider getting subscribed to our YouTube channel and press that bell icon to never miss any update from Simply learn. So, in this video, we will see what uninformed search is in AI. After that, we will cover some key features of uninformed search algorithms in AI. Moving forward, we will see an informed search in AI. After that, we will cover some key features of informed search algorithms in AI. Lastly, we will see the difference between uninformed and informed searches algorithm. By the end of this video, I can ensure you that all your questions and doubts related to informed and uninformed searches will have been cleared. On that note, if you are an aspiring AML engineer, then accelerate your career in AML with our comprehensive post graduate program in AI and machine learning. Boost your career with this AI and ML course, delivered in collaboration with Purdue University and IBM. Learn in-demand skills such as machine learning, deep learning, NLP, computer vision, reinforcement learning, generative AI, prompt engineering, chat GPT, and many more. You will receive a prestigious certificate and ask me anything session by IBM. With five capstones in different domains using real data sets, you will gain practical experience. Master classes by Purdue University and IBM expert ensure top notch education. Simplylearn job assist help you get noticed by leading companies. This programs cover statistics, Python, supervised and unsupervised learning, NLP, neural network, computer vision, GAANS, Keras, Tensor flow, and many more skills. Enroll now and unlock exciting AML opportunities. The link is in the description box below. So without any further ado, let's get started. So, what is uninformed search in AI? Uninformed search algorithm explore problem spaces without using heuristic information. They traverse states and like based solely on problem structure like Deffer search and Breath for search with completeness and simplicity but potentially sacrificing efficiency in large search spaces. Moving forward, let's see some features of uninformed search algorithm in AI. The first one is exclude additional information. Uninformed search algorithms navigate problem space solely based on the given problem. Disregarding any external information or heuristic guidance that might aid in efficient exploration. The second one is attains goal via action sequence length and order. Uninformed search determines solution by traversing through sequences of action without considering their individual merits, focusing instead on the order and the length of actions taken. The third one is lacks knowledge utilization for problem solving. So these algorithms do not exploit additional knowledge or insights about the problem domain. They rely solely on the problem structure element and available actions. The fourth one is typically in occurs higher cost than informed search. Uninformed search methods can let to substantial path resulting in potentially higher cost to reach the goal state when compared to informed search algorithm that leverage heuristic information. The fifth one is examples. BFS, DFS, Breath for search and Depth for search are classic examples of uninformed search algorithm that explore state and action without considering additional information making decisions solely based on their structural characteristics. So let's move forward and see what is informed search in AI? In AI, smart search methods called informed search use helpful clues to find solutions faster. They use extra information, like how far things are from the goal, to pick the best path to check first. This help them to reach solution more quickly and efficiently. Example is including A star and greedy base for search. They often enhance efficiency compared to uninformed search by narrowing down same direction potentially reducing the exploration time and the expanding new feature notes. However, the accuracy of heuristic information and its computational complexity can impact their performance. So some features of informed search algorithm in AI are. The first one is encompasses goal state information. Informed search method incorporate details about the desired code state allowing them algorithm to make more informed decision during the search process resulting in better path choices. The second one is enhance search efficiency. By utilizing heuristic information, informed search algorithm intelligently direct exploration towards more promising path.
[4:55]Leading to quicker convergence to solution and often reducing the overall search effort. The third one is harness knowledge for search implementation. These algorithms employ heuristic functions that estimate how close a given state is to the goal state. Helping prioritize states that are likely to lead solution. The fourth one is generally lower cost. Informed search approaches such as A star search usually lead to lower cost both in terms of time and resources by focusing on path that are more likely to lead optimal solution. The fifth one is requires less time for search. The use of heuristic information allows informed search to efficiently eliminate unpromising search direction leading to faster identification of solution especially in complex problem spaces. Moving forward, let's see some difference between informed search and uninformed search. So the first parameter is utilizing knowledge. So in informed search, employs knowledge during the search process. And in uninformed search does not require knowledge during the search. The second parameter is speed. In informed search, solution finding is quicker. And in uninformed search, solution finding is comparatively slower. The third parameter is completion. In informed search, it can be both complete and incomplete. And in uninformed search, always bound to be complete. And the fourth one is consumption of time. In informed search, due to the quicker search, it consumes less time. And in uninformed search, due to slower searches, it consumes more time. The fifth one is cost. So in informed search, expenses are much lower. As compared to uninformed search, expenses are comparatively higher. And the sixth one is direction. AI receives suggestion for solution in informed search. And in uninformed search, AI lacks suggestion for the solution direction. And the next one is efficiency. Costs less generate quicker results in informed search and in uninformed search costs more generate slower results. And the next one is length of implementation. So here implementation is shorter. And other side implementation is lengthier. And the last one is example. Informed search examples are graph search, greedy search. And in uninformed search, BFS and DFS, breadth for search and depth for search. In summary, uninformed search relies solely on the problem structure and action. While informed search leverages heuristic information to guide the search process more efficiently and effectively. So and with that, we have come to end of this video on uninformed search versus informed search. I hope you found this valuable and entertaining. Please ask any question about the topics covers in this video in comments section below. Our team of experts will assist you in addressing your problem. Thank you for watching. Stay safe, keep learning with Simplylearn.
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