UNIT-1 QB_(ANS).pdf

Subject : AI Unit 1 : Questions Q1. Elaborate Artificial Intelligence with suitable example along with it’s application. ANS: 1. AI is one of the newest sciences that holds a tendency to cause a machine to work as a human. 2. AI work started in earne...

Subject : AI Unit 1 : Questions Q1. Elaborate Artificial Intelligence with suitable example along with it’s application. ANS: 1. AI is one of the newest sciences that holds a tendency to cause a machine to work as a human. 2. AI work started in earnest after World War II, and the name itself was coined in 1956. 3. AI currently encompasses a huge variety of subfields , ranging from general purpose ares such as learning and perception to such specific task as playing chess , proving mathematical theorems , writing poetry and diagnosing diseases. 4. AI systematizes and automates intellectual tasks and is therefore potentially relevant to human intellectual activity. 5. Artificial Intelligence is composed of two words Artificial and Intelligence, where Artificial defines "man- made," and intelligence defines "thinking power", hence AI means "a man-made thinking power." 6. "It is a branch of computer science by which we can create intelligent machines which can behave like a human, think like humans, and able to make decisions." 7. Artificial Intelligence exists when a machine can have human based skills such as learning, reasoning, and solving problems 8. With Artificial Intelligence you do not need to preprogram a machine to do some work, despite that you can create a machine with programmed algorithms which can work with own intelligence, and that is the awesomeness of AI. 9. Artificial Intelligence (AI) is machine-displayed intelligence that simulates human behavior or thinking and can be trained to solve specific problems. 10. It is believed that AI is not a new technology, and some people says that as per Greek myth, there were Mechanical men in early days which can work and behave like humans. 11. AI is nothing a system that think like humans: “The exciting new effort to make computer think.. machines withn minds, in the full and literal sense.” (Haugeland, 1985). 12. First, AI is a system that can think like a human. Thinking humanly means cognitive modelling. 13. Cognitive modeling is an area of computer science that deals with simulating human problem-solving and mental processing in a computerized model. 14. “The activities that we associate with human thinking , activities such as decision making , problem solving, learning...”(Bellman , 1978). 15. A System that act like humans: “The art of creating machines that perform functions that require intelligence when performed by people.” (JKurzweil, 1990) 16. If the system reacts the same way as humans do, then we can consider that system is an AI. 17. “System that think rationally: the study of the computations that make it possible to perceive, reason and act.”(Winston, 1992) 18. It provides precise notations to express facts of the real world. 19. System that act rationally: Study of design of Intelligents Agents. 20. AI agent is the one who decide what to do and then perform action by receiving percepts from the environment. 21. Building a machine which can perform tasks that requires human intelligence such as: ⚫ Proving a theorem ⚫ Playing chess ⚫ Plan some surgical operation ⚫ Driving a car in traffic ⚫ Creating some system which can exhibit intelligent behavior, learn new things by itself, demonstrate, explain, and can advise to its user. 22. With the help of AI, you can create such software or devices which can solve real-world problems very easily and with accuracy such as health issues, marketing, traffic issues, etc. 23. With the help of AI, you can create your personal virtual Assistant, such as Cortana, Google Assistant, Siri, etc. 24. You can build such Robots which can work in an environment where survival of humans can be at risk. 25. AI opens a path for other new technologies, new devices, and new Opportunities. 26. Here is the list of AI Applications: AI Application in E-Commerce 1. Personalized Shopping Artificial Intelligence technology is used to create recommendation engines through which you can engage better with your customers.  These recommendations are made in accordance with their browsing history, preference, and interests. It helps in improving your relationship with your customers and their loyalty towards your brand. 2. AI-Powered Assistants Virtual shopping assistants and chatbots help improve the user experience while shopping online. Natural Language Processing is used to make the conversation sound as human and personal as possible. Moreover, these assistants can have real-time engagement with your customers. Did you know that on amazon.com, soon, customer service could be handled by chatbots? 3. Fraud Prevention Credit card frauds and fake reviews are two of the most significant issues that E-Commerce companies deal with. By considering the usage patterns, AI can help reduce the possibility of credit card fraud taking place. Many customers prefer to buy a product or service based on customer reviews. AI can help identify and handle fake reviews. Applications Of Artificial Intelligence in Education Although the education sector is the one most influenced by humans, Artificial Intelligence has slowly begun to seep its roots into the education sector as well. Even in the education sector, this slow transition of Artificial Intelligence has helped increase productivity among faculties and helped them concentrate more on students than office or administration work. Some of these applications in this sector include: 1. Administrative Tasks Automated to Aid Educators Artificial Intelligence can help educators with non-educational tasks like task-related duties like facilitating and automating personalized messages to students, back-office tasks like grading paperwork, arranging and facilitating parent and guardian interactions, routine issue feedback facilitating, managing enrollment, courses, and HR-related topics. 2. Creating Smart Content Digitization of content like video lectures, conferences, and textbook guides can be made using Artificial Intelligence. We can apply different interfaces like animations and learning content through customization for students from different grades. Artificial Intelligence helps create a rich learning experience by generating and providing audio and video summaries and integral lesson plans. 3. Voice Assistants Without even the direct involvement of the lecturer or the teacher, a student can access extra learning material or assistance through Voice Assistants. Through this, printing costs of temporary handbooks and also provide answers to very common questions easily. Applications of Artificial Intelligence in Human Resource: Did you know that companies use intelligent software to ease the hiring process? Artificial Intelligence helps with blind hiring. Using machine learning software, you can examine applications based on specific parameters. AI drive systems can scan job candidates' profiles, and resumes to provide recruiters an understanding of the talent pool they must choose from. Applications of Artificial Intelligence in Healthcare: Artificial Intelligence finds diverse applications in the healthcare sector. AI applications are used in healthcare to build sophisticated machines that can detect diseases and identify cancer cells. Artificial Intelligence can help analyze chronic conditions with lab and other medical data to ensure early diagnosis. AI uses the combination of historical data and medical intelligence for the discovery of new drugs. Q2. Discuss the historical evaluation of Artificial Intelligence. ANS: Refer this below given link fo this particular answer: https://www.javatpoint.com/history-of-artificial-intelligence Q3. Discuss the application of AI. ANS: ⚫ Applications of Artificial Intelligence in Marketing: Artificial Intelligence (AI) applications are popular in the marketing domain as well. Using AI, marketers can deliver highly targeted and personalized ads with the help of behavioral analysis, and pattern recognition in ML, etc. It also helps with retargeting audiences at the right time to ensure better results and reduced feelings of distrust and annoyance. AI can help with content marketing in a way that matches the brand's style and voice. It can be used to handle routine tasks like performance, campaign reports, and much more. AI can provide users with real-time personalizations based on their behavior and can be used to edit and optimize marketing campaigns to fit a local market's needs. ⚫ Applications of Artificial Intelligence in Chatbots AI chatbots can comprehend natural language and respond to people online who use the "live chat" feature that many organizations provide for customer service. AI chatbots are effective with the use of machine learning and can be integrated in an array of websites and applications. AI chatbots can eventually build a database of answers, in addition to pulling information from an established selection of integrated answers. As AI continues to improve, these chatbots can effectively resolve customer issues, respond to simple inquiries, improve customer service, and provide 24/7 support. All in all, these AI chatbots can help to improve customer satisfaction. ⚫ AI in Data Security: Many people believe that Artificial Intelligence (AI) is the present and future of the technology sector. Many industry leaders employ AI for a variety of purposes, including providing valued services and preparing their companies for the future. Data security, which is one of the most important assets of any tech- oriented firm, is one of the most prevalent and critical applications of AI. With confidential data ranging from consumer data (such as credit card information) to organizational secrets kept online, data security is vital for any institution to satisfy both legal and operational duties. This work is now as difficult as it is vital, and many businesses deploy AI-based security solutions to keep their data out of the wrong hands. Because the world is smarter and more connected than ever before, the function of Artificial Intelligence in business is critical today. According to several estimates, cyberattacks will get more tenacious over time, and security teams will need to rely on AI solutions to keep systems and data under control. 1. dentifies Unknown Threats A human may not be able to recognize all of the hazards that a business confronts. Every year, hackers launch hundreds of millions of assaults for a variety of reasons. Unknown threats can cause severe network damage. Worse, they can have an impact before you recognize, identify, and prevent them. As attackers test different tactics ranging from malware assaults to sophisticated malware assaults, contemporary solutions should be used to avoid them. Artificial Intelligence has shown to be one of the most effective security solutions for mapping and preventing unexpected threats from wreaking havoc on a corporation. 2. Flaw Identification AI assists in detecting data overflow in a buffer. When programs consume more data than usual, this is referred to as buffer overflow. Aside from the fault caused by human triggers breaking crucial data. These blunders are also observable by AI, and they are detected in real- time, preventing future dangers. AI can precisely discover cybersecurity weaknesses, faults, and other problems using Machine Learning. Machine Learning also assists AI in identifying questionable data provided by any application. Malware or virus used by hackers to gain access to systems as well as steal data is carried out via programming language flaws. 3. Threat Prevention Artificial Intelligence technology is constantly being developed by cyber security vendors. In its advanced version, AI is designed to detect flaws in the system or even the update. It’d instantly exclude anybody attempting to exploit those issues. AI would be an outstanding tool for preventing any threat from occurring. It may install additional firewalls as well as rectify code faults that lead to dangers. 4. Responding to Threats It's something that happens after the threat has entered the system. As previously explained, AI is used to detect unusual behavior and create an outline of viruses or malware. AI is currently taking appropriate action against viruses or malware. The reaction consists mostly of removing the infection, repairing the fault, and administering the harm done. Finally, AI guarantees that such an incident does not happen again and takes proper preventative actions. ⚫ AI in Travel and Transport: Intelligent technology has become a part of our daily lives in recent years. And, as technology advances across society, new uses of AI, notably in transportation, are becoming mainstream. This has created a new market for firms and entrepreneurs to develop innovative solutions for making public transportation more comfortable, accessible, and safe. Intelligent transportation systems have the potential to become one of the most effective methods to improve the quality of life for people all around the world. There are multiple instances of similar systems in use in various sectors. 1. Heavy Goods Transportation Truck platooning, which networks HGV (heavy goods vehicles), for example, might be extremely valuable for vehicle transport businesses or for moving other large items. The lead vehicle in a truck platoon is steered by a human driver, however, the human drivers in any other trucks drive passively, just taking the wheel in exceptionally dangerous or difficult situations. Because all of the trucks in the platoon are linked via a network, they travel in formation and activate the actions done by the human driver in the lead vehicle at the same time. So, if the lead driver comes to a complete stop, all of the vehicles following him do as well. 2. Traffic Management Clogged city streets are a key impediment to urban transportation all around the world. Cities throughout the world have enlarged highways, erected bridges, and established other modes of transportation such as train travel, yet the traffic problem persists. However, AI advancements in traffic management provide a genuine promise of changing the situation. Intelligent traffic management may be used to enforce traffic regulations and promote road safety. For example, Alibaba's City Brain initiative in China uses AI technologies such as predictive analysis, big data analysis, and a visual search engine in order to track road networks in real-time and reduce congestion. Building a city requires an efficient transformation system, and AI-based traffic management technologies are powering next-generation smart cities. 3. Ride-Sharing Platforms like Uber and OLA leverage AI to improve user experiences by connecting riders and drivers, improving user communication and messaging, and optimizing decision-making. For example, Uber has its own proprietary ML-as-a-service platform called Michelangelo that can anticipate supply and demand, identify trip abnormalities like wrecks, and estimate arrival timings. 4. Route Planning AI-enabled route planning using predictive analytics may help both businesses and people. Ride-sharing services already achieve this by analyzing numerous real-world parameters to optimize route planning. AI-enabled route planning is a terrific approach for businesses, particularly logistics and shipping industries, to construct a more efficient supply network by anticipating road conditions and optimizing vehicle routes. Predictive analytics in route planning is the intelligent evaluation by a machine of a number of road usage parameters such as congestion level, road restrictions, traffic patterns, consumer preferences, and so on. Cargo logistics companies, such as vehicle transport services or other general logistics firms, may use this technology to reduce delivery costs, accelerate delivery times, and better manage assets and operations. ⚫ AI Application in E-Commerce 1. Personalized Shopping Artificial Intelligence technology is used to create recommendation engines through which you can engage better with your customers. These recommendations are made in accordance with their browsing history, preference, and interests. It helps in improving your relationship with your customers and their loyalty towards your brand. 2. AI-Powered Assistants Virtual shopping assistants and chatbots help improve the user experience while shopping online. Natural Language Processing is used to make the conversation sound as human and personal as possible. Moreover, these assistants can have real-time engagement with your customers. Did you know that on amazon.com, soon, customer service could be handled by chatbots? 3. Fraud Prevention Credit card frauds and fake reviews are two of the most significant issues that E-Commerce companies deal with. By considering the usage patterns, AI can help reduce the possibility of credit card fraud taking place. Many customers prefer to buy a product or service based on customer reviews. AI can help identify and handle fake reviews. ⚫ Applications Of Artificial Intelligence in Education Although the education sector is the one most influenced by humans, Artificial Intelligence has slowly begun to seep its roots into the education sector as well. Even in the education sector, this slow transition of Artificial Intelligence has helped increase productivity among faculties and helped them concentrate more on students than office or administration work. Some of these applications in this sector include: 1. Administrative Tasks Automated to Aid Educators Artificial Intelligence can help educators with non-educational tasks like task-related duties like facilitating and automating personalized messages to students, back-office tasks like grading paperwork, arranging and facilitating parent and guardian interactions, routine issue feedback facilitating, managing enrollment, courses, and HR-related topics. 2. Creating Smart Content Digitization of content like video lectures, conferences, and textbook guides can be made using Artificial Intelligence. We can apply different interfaces like animations and learning content through customization for students from different grades. Artificial Intelligence helps create a rich learning experience by generating and providing audio and video summaries and integral lesson plans. 3. Voice Assistants Without even the direct involvement of the lecturer or the teacher, a student can access extra learning material or assistance through Voice Assistants. Through this, printing costs of temporary handbooks and also provide answers to very common questions easily. ⚫ Applications of Artificial Intelligence in Healthcare: Artificial Intelligence finds diverse applications in the healthcare sector. AI applications are used in healthcare to build sophisticated machines that can detect diseases and identify cancer cells. Artificial Intelligence can help analyze chronic conditions with lab and other medical data to ensure early diagnosis. AI uses the combination of historical data and medical intelligence for the discovery of new drugs. 1. Robotic Surgery: Robotic operations have a very small margin of error and can operate 24 hours a day, seven days a week without becoming weary. They are less intrusive than previous procedures because they work with such precision, potentially reducing the amount of time patients spend in the hospital recovering. 2. Assisted Diagnosis: AI can now interpret MRI scans to check for tumours and other harmful growths at a tenfold faster rate than radiologists can, with a much narrower margin of error, thanks to computer vision and convolutional neural networks. Q4. Explain the concept of Intelligent agents. What are the characteristics of Intelligent Agents? ANS: This agent has some level of autonomy that allows it to perform specific, predictable, and repetitive tasks for users or applications. It’s also termed as ‘intelligent’ because of its ability to learn during the process of performing tasks. The two main functions of intelligent agents include perception and action. Perception is done through sensors while actions are initiated through actuators. Intelligent agents consist of sub-agents that form a hierarchical structure. Lower-level tasks are performed by these sub-agents. The higher-level agents and lower-level agents form a complete system that can solve difficult problems through intelligent behaviors or responses. The structure of intelligent agents The IA structure consists of three main parts: architecture, agent function, and agent program. Architecture: This refers to machinery or devices that consists of actuators and sensors. The intelligent agent executes on this machinery. Examples include a personal computer, a car, or a camera. Agent function: This is a function in which actions are mapped from a certain percept sequence. Percept sequence refers to a history of what the intelligent agent has perceived. Agent program: This is an implementation or execution of the agent function. The agent function is produced through the agent program’s execution on the physical architecture. Working of Intelligent Agents: Intelligent agents work through three main components: sensors, actuators, and effectors. Getting an overview of these components can improve our understanding of how intelligent agents work.  Sensors: These are devices that detect any changes in the environment. This information is sent to other devices. In artificial intelligence, the environment of the system is observed by intelligent agents through sensors. Actuators: These are components through which energy is converted into motion. They perform the role of controlling and moving a system. Examples include rails, motors, and gears. Effectors: The environment is affected by effectors. Examples include legs, fingers, wheels, display screen, and arms. The following diagram shows how these components are positioned in the AI system. Intelligent Agents: An intelligent agent is an autonomous entity which act upon an environment using sensors and actuators for achieving goals. An intelligent agent may learn from the environment to achieve their goals. A thermostat is an example of an intelligent agent. Following are the main four rules for an AI agent: o Rule 1: An AI agent must have the ability to perceive the environment. o Rule 2: The observation must be used to make decisions. o Rule 3: Decision should result in an action. o Rule 4: The action taken by an AI agent must be a rational action. Characteristics of intelligent agents Intelligent agents have the following distinguishing characteristics:  They have some level of autonomy that allows them to perform certain tasks on their own. They have a learning ability that enables them to learn even as tasks are carried out. They can interact with other entities such as agents, humans, and systems. New rules can be accommodated by intelligent agents incrementally. They exhibit goal-oriented habits. They are knowledge-based. They use knowledge regarding communications, processes, and entities. Q5. Explain the four approaches of AI. ANS: ) 1. Acting Humanly: Turing Test: For testing intelligence Alan Turing (1950) proposed a test called as Turing test. He suggested a test based on common features that can match with the most intelligent entity human beings. Computer would need to possess following capabilities: a) Natural language processing - To enable it to communicate successfully in English. b) Knowledge representation to store what it knows, what it hears. c) Automated reasoning to make use of stored information to answer questions being asked and to draw conclusions. d) Machine learning to adapt to new circumstances and to detect and make new predictions by finding patterns. 2. Thinking Humanly: Thinking humanly means trying to understand and model how the human mind works. As we are saying that the given program thinks like human , we should know that how human thinks. For that, the theory of human minds needs to be explored. There are two ways to do this: through introspection i.e. trying to catch our own thoughts as they go by and through psychological experiments. 3. Thinking Rationally the "laws of thought approach": The concept of "Right thinking" was proposed by Aristotle. This idea provided patterns for argument structures that always yielded correct conclusions when given correct premises. For example, "Ram is man", "All men are mortal", "Ram is mortal".. These laws of thought were supposed to govern the operation in the mind; their study initiated the field called logic which can be implemented to create intelligent systems. 4. Acting rationally: The rational agent approach: An agent is just something that acts (agent comes from the Latin agere, to do). But computer agents are expected to have other attributes that distinguish them from mere "programs," such as operating under autonomous control, perceiving their environment, persisting over a prolonged time period, adapting to change, and being capable of taking on another's goals. A rational agent is one that acts so as to achieve the best outcome or, when there is uncertainty, the best expected outcome. In the "laws of thought" approach to AI, the emphasis was on correct inferences. Mak- ing correct inferences is sometimes part of being a rational agent, because one way to act rationally is to reason logically to the conclusion that a given action will achieve one's goals and then to act on that conclusion. On the other hand, correct inference is not all of ratio- nality, because there are often situations where there is no provably correct thing to do, yet something must still be done. Q6. Explain Simple Reflex Agent and Model Base Agents. ANS: Refer this following link given below: https://www.javatpoint.com/types-of-ai-agents Q7. Describe Goal based Agents along with the Neat Labelled Diagram. ANS: Refer this following link given below: https://www.javatpoint.com/types-of-ai-agents Q8. What is Learning Agents? Explain the conceptual components used with Neat Labelled Diagram. ANS: Refer this following link given below: https://www.javatpoint.com/types-of-ai-agents Q9. Write a short note on Turing Test. ANS: Refer this following link given below: https://www.javatpoint.com/turing-test-in-ai Q10. Draw and describe the architecture of Utility Based Agent. How is it different from Model Based Agent. ANS: Refer this following link given below: https://www.javatpoint.com/types-of-ai-agents Q11. Give state space representation for 8 Puzzle Problem. What are the possible Heuristic functions for it? Solution: The 8 puzzle consists of eight numbered, movable tiles set in a 3x3 frame. One cell of the frame is always empty thus making it possible to move an adjacent numbered tile into the empty cell. Such a puzzle is illustrated in following diagram. The program is to change the initial configuration into the goal configuration. A solution to the problem is an appropriate sequence of moves, such as “move tile 5 to the right, move tile 7 to the left, move tile 6 to the down” etc… To solve a problem, we must specify the global database, the rules, and the control strategy. For the 8 puzzle problem that correspond to three components. These elements are the problem states, moves and goal. In this problem each tile configuration is a state. The set of all possible configuration in the problem space, consists of 3,62,880 different configurations of the 8 tiles and blank space. For the 8-puzzle, a straight forward description is a 3X3 array of matrix of numbers. Initial global database is this description of the initial problem state. Virtually any kind of data structure can be used to describe states. A move transforms one problem state into another state. Figure 1: Solution of 8 Puzzle problem The 8-puzzle is conveniently interpreted as having the following for moves. Move empty space (blank) to the left, move blank up, move blank to the right and move blank down. These moves are modeled by production rules that operate on the state descriptions in the appropriate manner. The goal condition forms the basis for the termination. The control strategy repeatedly applies rules to state descriptions until a description of a goal state is produced. It also keeps track of rules that have been applied so that it can compose them into sequence representing the problem solution. A solution to the 8-puzzle problem is given in the above figure 1. Q12. Discuss the Problem Solving Agent by Searching Algorithm in detail. ANS: Refer the below given link: https://www.javatpoint.com/search-algorithms-in-ai You have to refer the above link till space complexity after that continue with answer what i have mentioned below. Types of search algorithms: Based on the search problems we can classify the search algorithms into uninformed (Blind search) search and informed search (Heuristic search) algorithms. Uninformed/Blind Search: The uninformed search does not contain any domain knowledge such as closeness, the location of the goal. It operates in a brute-force way as it only includes information about how to traverse the tree and how to identify leaf and goal nodes. Uninformed search applies a way in which search tree is searched without any information about the search space like initial state operators and test for the goal, so it is also called blind search.It examines each node of the tree until it achieves the goal node. It can be divided into two main types: o Breadth-first search o Depth-first search Informed Search Informed search algorithms use domain knowledge. In an informed search, problem information is available which can guide the search. Informed search strategies can find a solution more efficiently than an uninformed search strategy. Informed search is also called a Heuristic search. A heuristic is a way which might not always be guaranteed for best solutions but guaranteed to find a good solution in reasonable time. Informed search can solve much complex problem which could not be solved in another way. An example of informed search algorithms is a traveling salesman problem.  1. Greedy Search 2. A* Search Q13. Explain Uninformed Search Algorithm. ANS: Uninformed Search (also called Blind Search). The term means that they have no additional information about states beyond that provided in the problem definition or additional information about state or search space other than how to traverse the tree, so it is also called blind search. Uninformed search is a class of general-purpose search algorithms which operates in brute force-way. All they can do is generate successors and distinguish a goal state from a nongoal state. Strategies that know whether one non- goal state is "more promising" than another are called Informed Search or Heuristic Search Strategies. It can be divided into two main types: o Breadth-first search o Depth-first search Breadth-first Search: ⚫ Breadth-first search is the most common search strategy for traversing a tree or graph. ⚫ This algorithm searches breadthwise in a tree or graph, so it is called breadth-first search. ⚫ BFS algorithm starts searching from the root node of the tree and expands all successor node at the current level before moving to nodes of next level. ⚫ The breadth-first search algorithm is an example of a general-graph search algorithm. ⚫ Breadth-first search implemented using FIFO queue data structure. Advantages: ⚫ BFS will provide a solution if any solution exists. ⚫ If there are more than one solutions for a given problem, then BFS will provide the minimal solution which requires the least number of steps. Disadvantages: ⚫ It requires lots of memory since each level of the tree must be saved into memory to expand the next level. ⚫ BFS needs lots of time if the solution is far away from the root node. Mention one algorithm that we have done it in the lecture. Depth-first Search ⚫ Depth-first search isa recursive algorithm for traversing a tree or graph data structure. ⚫ It is called the depth-first search because it starts from the root node and follows each path to its greatest depth node before moving to the next path. ⚫ DFS uses a stack data structure for its implementation. ⚫ The process of the DFS algorithm is similar to the BFS algorithm. Advantage: ⚫ DFS requires very less memory as it only needs to store a stack of the nodes on the path from root node to the current node. ⚫ It takes less time to reach to the goal node than BFS algorithm (if it traverses in the right path). Disadvantage: ⚫ There is the possibility that many states keep re-occurring, and there is no guarantee of finding the solution. ⚫ DFS algorithm goes for deep down searching and sometime it may go to the infinite loop. Q14. Explain Informed Search Algorithm and express its heuristic function. ANS: Informed search algorithm contains an array of knowledge such as how far we are from the goal, path cost, how to reach to goal node, etc. This knowledge help agents to explore less to the search space and find more efficiently the goal node. The informed search algorithm is more useful for large search space. Informed search algorithm uses the idea of heuristic, so it is also called Heuristic search. Heuristics function: Heuristic is a function which is used in Informed Search, and it finds the most promising path. It takes the current state of the agent as its input and produces the estimation of how close agent is from the goal. The heuristic method, however, might not always give the best solution, but it guaranteed to find a good solution in reasonable time. Heuristic function estimates how close a state is to the goal. It is represented by h(n), and it calculates the cost of an optimal path between the pair of states. The value of the heuristic function is always positive. Admissibility of the heuristic function is given as: h(n)