Description : Which of the following is the component of learning system? a) Goal b) Model c) Learning rules d) All of the mentioned
Last Answer : d) All of the mentioned
Description : Which of the following is the model used for learning? a) Decision trees b) Neural networks c) Propositional and FOL rules d) All of the mentioned
Description : The component of an ICAI (Intelligent Computer Assisted Instruction) presenting information to the student is the? a) Student model b) Problem solving expertise c) Tutoring module d) All of the mentioned
Last Answer : c) Tutoring module
Description : Shaping teaching techniques to fit the learning patterns of individual students is the goal of __________ a) decision support b) automatic programming c) intelligent computer-assisted instruction d) expert systems
Last Answer : c) intelligent computer-assisted instruction
Description : In ____ the goal is for the software to use what it has learned in one area to solve problems in other areas. A. Machine Learning B. Deep Learning C. Neural Networks D. None of these
Last Answer : B. Deep Learning
Description : Point out the correct statement. a) With PaaS, the goal is to create hosted scalable applications that are used in a Software as a Service model b) Applications built using PaaS tools need to ... , the data and transaction management conforms to the business rules you create d) All of the mentioned
Last Answer : All of the mentioned
Description : Point out the correct statement. a) With PaaS, the goal is to create hosted scalable applications that are used in a Software as a Service model b) Applications built using PaaS tools need to ... the data and transaction management conforms to the business rules you create d) All of the mentioned
Description : Which algorithm will work backward from the goal to solve a problem? a) Forward chaining b) Backward chaining c) Hill-climb algorithm d) None of the mentioned
Last Answer : b) Backward chaining
Description : Which approach is to pretend that a pure divide and conquer algorithm will work? a) Goal independence b) Subgoal independence c) Both Goal & Subgoal independence d) None of the mentioned
Last Answer : b) Subgoal independence
Description : What among the following constitutes to the incremental formulation of CSP? a) Path cost b) Goal cost c) Successor function d) All of the mentioned
Description : A heuristic is a way of trying ___________ a) To discover something or an idea embedded in a program b) To search and measure how far a node in a search tree seems to be from a goal c) To compare two nodes in a search tree to see if one is better than another d) All of the mentioned
Description : Which search method will expand the node that is closest to the goal? a) Best-first search b) Greedy best-first search c) A* search d) None of the mentioned
Last Answer : b) Greedy best-first search
Description : What is the main task of a problem-solving agent? a) Solve the given problem and reach to goal b) To find out which sequence of action will get it to the goal state c) All of the mentioned d) None of the mentioned
Last Answer : c) All of the mentioned
Description : When do we call the states are safely explorable? a) A goal state is unreachable from any state b) A goal state is denied access c) A goal state is reachable from every state d) None of the mentioned
Last Answer : c) A goal state is reachable from every state
Description : A heuristic is a way of trying __________ a) To discover something or an idea embedded in a program b) To search and measure how far a node in a search tree seems to be from a goal c) To compare two nodes in a search tree to see if one is better than the other is d) All of the mentioned
Description : Evolutionary computation is A . Combining different types of method or information B. Approach to the design of learning algorithms that is structured along the lines of the theory of evolution. C. ... the knowledge of an expert formulated in terms of if-then rules. D . None of these
Last Answer : B. Approach to the design of learning algorithms that is structured along the lines of the theory of evolution.
Description : Expert systems A . Combining different types of method or information B. Approach to the design of learning algorithms that is structured along the lines of the theory of evolution C. an information base ... the knowledge of an expert formulated in terms of if-then rules D . None of these
Last Answer : C. an information base filled with the knowledge of an expert formulated in terms of if-then rules
Description : Which of the following, is a component of an expert system? a) inference engine b) knowledge base c) user interface d) all of the mentioned
Last Answer : d) all of the mentioned
Description : Which of the following is an example of active learning? a) News Recommender system b) Dust cleaning machine c) Automated vehicle d) None of the mentioned
Last Answer : a) News Recommender system
Description : Following is an example of active learning: a) News Recommender system b) Dust cleaning machine c) Automated vehicle d) None of the mentioned
Description : What is the major component/components for measuring the performance of problem solving? a) Completeness b) Optimality c) Time and Space complexity d) All of the mentioned
Description : ____________ planning allows the agent to take advice from the domain designer in the form of decomposition rules. a) GraphPlan b) Hierarchical task network (HTN) c) SatPlan d) None of the mentioned
Last Answer : b) Hierarchical task network (HTN)
Description : A Personal Consultant knowledge base contain information in the form of __________ a) parameters b) contexts c) production rules d) all of the mentioned
Description : Fuzzy logic is usually represented as a) IF-THEN-ELSE rules b) IF-THEN rules c) Both a & b d) None of the mentioned
Last Answer : b) IF-THEN rules
Description : Which is used to choose among multiple consistent hypotheses? a) Razor b) Ockham razor c) Learning element d) None of the mentioned
Last Answer : b) Ockham razor
Description : What is used in determining the nature of the learning problem? a) Environment b) Feedback c) Problem d) All of the mentioned
Last Answer : b) Feedback
Description : Which modifies the performance element so that it makes better decision? a) Performance element b) Changing element c) Learning element d) None of the mentioned
Last Answer : c) Learning element
Description : Which method is used to search better by learning? a) Best-first search b) Depth-first search c) Metalevel state space d) None of the mentioned
Last Answer : c) Metalevel state space
Description : Which is used to provide the feedback to the learning element? a) Critic b) Actuators c) Sensor d) None of the mentioned
Last Answer : a) Critic
Description : Which is used to improve the agents performance? a) Perceiving b) Learning c) Observing d) None of the mentioned
Last Answer : b) Learning
Description : In which agent does the problem generator is present? a) Learning agent b) Observing agent c) Reflex agent d) None of the mentioned
Last Answer : a) Learning agent
Description : The performance of an agent can be improved by __________ a) Learning b) Observing c) Perceiving d) None of the mentioned
Last Answer : a) Learning
Description : Which of the following is not an application of learning? a) Data mining b) WWW c) Speech recognition d) None of the mentioned
Last Answer : d) None of the mentioned
Description : Which agent deals with happy and unhappy states? a) Simple reflex agent b) Model based agent c) Learning agent d) Utility based agent
Last Answer : d) Utility based agent
Description : Which are partially captured by triphone model? a) Articulation effects b) Coarticulation effects c) Both Articulation & Coarticulation effects d) None of the mentioned
Last Answer : b) Coarticulation effects
Description : Which is used to capture the internal structure of the phones? a) One-state phone model b) Two-state phone model c) Three-state phone mone d) All of the mentioned
Last Answer : c) Three-state phone mone
Description : Which of the following are the advantage/s of Decision Trees? a) Possible Scenarios can be added b) Use a white box model, If given result is provided by a model c) Worst, best and expected values can be determined for different scenarios d) All of the mentioned
Description : Where does the Hidden Markov Model is used? a) Speech recognition b) Understanding of real world c) Both Speech recognition & Understanding of real world d) None of the mentioned
Last Answer : a) Speech recognition
Description : Where does the additional variables are added in HMM? a) Temporal model b) Reality model c) Probability model d) All of the mentioned
Last Answer : a) Temporal model
Description : What is the problem space of means-end analysis? a) An initial state and one or more goal states b) One or more initial states and one goal state c) One or more initial states and one or more goal state d) One initial state and one goal state
Last Answer : a) An initial state and one or more goal states
Description : Forward chaining systems are _____________ where as backward chaining systems are ___________ a) Goal-driven, goal-driven b) Goal-driven, data-driven c) Data-driven, goal-driven d) Data-driven, data-driven
Last Answer : c) Data-driven, goal-driven
Description : Flexible CSPs relax on _______ a) Constraints b) Current State c) Initial State d) Goal State
Last Answer : a) Constraints
Description : Searching using query on Internet is, use of ___________ type of agent. a) Offline agent b) Online agent c) Both Offline & Online agent d) Goal Based & Online agent
Last Answer : d) Goal Based & Online agent
Description : A complete, local search algorithm always finds goal if one exists, an optimal algorithm always finds a global minimum/maximum. a) True b) False
Last Answer : a) True
Description : A* is optimal if h(n) is an admissible heuristic-that is, provided that h(n) never underestimates the cost to reach the goal. a) True b) False
Description : Greedy search strategy chooses the node for expansion in ___________ a) Shallowest b) Deepest c) The one closest to the goal node d) Minimum heuristic cost
Last Answer : c) The one closest to the goal node
Description : Heuristic function h(n) is ________ a) Lowest path cost b) Cheapest path from root to goal node c) Estimated cost of cheapest path from root to goal node d) Average path cost
Last Answer : c) Estimated cost of cheapest path from root to goal node