Give example for real world end toy problems.

1 Answer

Answer :

Real world problem examples:

i. Airline travel problem.

ii. Touring problem.

iii. Traveling salesman problem.

iv. VLSI Layout problem

v. Robot navigation

vi. Automatic Assembly

vii. Internet searching

 Toy problem Examples:

 Vacuum world problem.

 8 – Queen problem

 8 – Puzzle problem

Related questions

Description : Give example problems for Artificial Intelligence. 

Last Answer : i. Toy problems ii. Real world problems

Description : What are the advantages of neural networks over conventional computers? (i) They have the ability to learn by example (ii) They are more fault tolerant (iii)They are more suited for real time operation due to their high ... true b) (i) and (iii) are true c) Only (i) d) All of the mentioned

Last Answer : d) All of the mentioned

Description : What are the advantages of neural networks over conventional computers? (i) They have the ability to learn by example (ii) They are more fault tolerant (iii)They are more suited for real time operation due to their high ... true b) (i) and (iii) are true c) Only (i) d) All of the mentioned

Last Answer : 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 : Neuro software is: a) A software used to analyze neurons b) It is powerful and easy neural network c) Designed to aid experts in real world d) It is software used by Neuro surgeon

Last Answer : b) It is powerful and easy neural network

Description : The expert system developed at MIT to solve mathematical problems is known as ___________ a) RAND b) ISIS c) MACSYMA d) MOLGEN

Last Answer : c) MACSYMA

Description : Decision trees are appropriate for the problems where ___________ a) Attributes are both numeric and nominal b) Target function takes on a discrete number of values. c) Data may have errors d) All of the mentioned

Last Answer : d) All of the mentioned

Description : An AI system developed by Daniel Bobrow to read and solve algebra word problems. a) SHRDLU b) SIMD c) BACON d) STUDENT

Last Answer : d) STUDENT

Description : Planning graphs works only for prepositional planning problems. a) True b) False

Last Answer : a) True

Description : Adversarial search problems uses ____________ a) Competitive Environment b) Cooperative Environment c) Neither Competitive nor Cooperative Environment d) Only Competitive and Cooperative Environment

Last Answer : a) Competitive Environment

Description : Constraint satisfaction problems on finite domains are typically solved using a form of ___________ a) Search Algorithms b) Heuristic Search Algorithms c) Greedy Search Algorithms d) All of the mentioned

Last Answer : d) All of the mentioned

Description : Which of the Following problems can be modeled as CSP? a) 8-Puzzle problem b) 8-Queen problem c) Map coloring problem d) All of the mentioned

Last Answer : d) All of the mentioned

Description : _______________ are mathematical problems defined as a set of objects whose state must satisfy a number of constraints or limitations. a) Constraints Satisfaction Problems b) Uninformed Search Problems c) Local Search Problems d) All of the mentioned

Last Answer : a) Constraints Satisfaction Problems

Description : The time and space complexity of BFS is (For time and space complexity problems consider b as branching factor and d as depth of the search tree.) a) O(bd+1) and O(bd+1) b) O(b2) and O(d2) c) O(d2) and O(b2) d) O(d2) and O(d2)

Last Answer : a) O(bd+1) and O(bd+1)

Description : People overcome natural language problems by _____________ a) grouping attributes into frames b) understanding ideas in context c) identifying with familiar situations d) both understanding ideas in context & identifying with familiar situations

Last Answer : d) both understanding ideas in context & identifying with familiar situations

Description : Membership function can be thought of as a technique to solve empirical problems on the basis of A. knowledge B. examples C. learning D. experience

Last Answer : D. experience

Description : ANN is composed of large number of highly interconnected processing elements(neurons) working in unison to solve problems. A. True B. False C. D.

Last Answer : A. True

Description : Decision trees are appropriate for the problems where: a) Attributes are both numeric and nominal b) Target function takes on a discrete number of values. c) Data may have errors d) All of the mentioned

Last Answer : d) All of the mentioned

Description : Having multiple perceptrons can actually solve the XOR problem satisfactorily: this is because each perceptron can partition off a linear part of the space itself, and they can then combine their results. ... have to be explicitly hand-coded d) False - just having a single perceptron is enough

Last Answer : c) True – perceptrons can do this but are unable to learn to do it – they have to be explicitly hand-coded

Description : Why are linearly separable problems of interest of neural network researchers? a) Because they are the only class of problem that network can solve successfully b) Because they are the only ... mathematical functions that are continue d) Because they are the only mathematical functions you can draw

Last Answer : b) Because they are the only class of problem that Perceptron can solve successfully

Description : What are the two sub problems in discourse understanding?

Last Answer : i. Reference Resolution  ii. The structure of coherent discourse.

Description : What are the things that agent knows in online search problems?

Last Answer : a. Actions(s) b. Step cost function C(s, a, s’) c. Goal TEST(s)

Description : Define Optimization Problems.

Last Answer :  The aim of this problem is to find the best state according to an objective function. 

Description : What is Released problems?

Last Answer :  A problem with fewer restrictions on the actions is called a relaxed problem. 

Description : PROLOG is an AI programming language which solves problems with a form of symbolic logic known as ______. A. Propositional logic B. Tautology C. Predicate calculus D. Temporal logic

Last Answer : C. Predicate calculus 

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 : ______ is a branch of computer science which deals with helping machines finds solutions to complex problems in a more human like fashions A. Artificial Intelligence B. Internet of Things C. Embedded System D. Cyber Security

Last Answer : A. Artificial Intelligence 

Description : Wumpus World is a classic problem, best example of _______ a) Single player Game b) Two player Game c) Reasoning with Knowledge d) Knowledge based Game

Last Answer : c) Reasoning with Knowledge

Description : In which of the following situations might a blind search be acceptable? a) Real life situation b) Complex game c) Small search space d) All of the mentioned

Last Answer : c) Small search space

Description : Which of the following task/tasks Artificial Intelligence could not do yet? a) Understand natural language robustly b) Web mining c) Construction of plans in real time dynamic systems d) All of the mentioned

Last Answer : d) All of the mentioned

Description : In which of the following situations might a blind search be acceptable? a) real-life situation b) complex game c) small search space d) all of the mentioned

Last Answer : c) small search space

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 : Which of the basic parts of a robot unit would include the computer circuitry that could be programmed to determine what the robot would do? a) sensor b) controller c) arm d) end effector

Last Answer : b) controller

Description : The number of moveable joints in the base, the arm, and the end effectors of the robot determines_________ a) degrees of freedom b) payload capacity c) operational limits d) flexibility

Last Answer : a) degrees of freedom

Description : Which of the following terms IS NOT one of the five basic parts of a robot? a) peripheral tools b) end effectors c) controller d) drive

Last Answer : a) peripheral tools

Description : End Nodes are represented by __________ a) Disks b) Squares c) Circles d) Triangles

Last Answer : d) Triangles

Description : Choose from the following that are Decision Tree nodes? a) Decision Nodes b) End Nodes c) Chance Nodes d) All of the mentioned

Last Answer : d) All of the mentioned

Description : Zero sum games are the one in which there are two agents whose actions must alternate and in which the utility values at the end of the game are always the same. a) True b) False

Last Answer : b) False

Description : A robot’s “arm” is also known as its __________ a) end effector b) actuator c) manipulator d) servomechanism

Last Answer : c) manipulator

Description : Which technique is being investigated as an approach to automatic programming? a) generative CAI b) specification by example c) non-hierarchical planning d) all of the mentioned

Last Answer : b) specification by example

Description : Susan is so beautiful; I bet she is smart too. This is an example of __________ a) The halo effect b) The primary effect c) A self-fulfilling prophecy d) The recency effect

Last Answer : a) The halo effect

Description : Which of the following is true? (i) On average, neural networks have higher computational rates than conventional computers. (ii) Neural networks learn by example. (iii) Neural networks mimic the way the human brain works. ... ) are true c) (i), (ii) and (iii) are true d) None of the mentioned

Last Answer : a) All of the mentioned are true

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 : Automated vehicle is an example of ______ a) Supervised learning b) Unsupervised learning c) Active learning d) Reinforcement learning

Last Answer : a) Supervised learning

Description : The famous spare tire problem or Scheduling classes for bunch of students or Air cargo transport are the best example of ____________ a) Planning problem b) Partial Order planning problem c) Total order planning d) None of the mentioned

Last Answer : a) Planning problem

Description : What among the following is/are the example of the intelligent agent/agents? a) Human b) Robot c) Autonomous Spacecraft d) All of the mentioned

Last Answer : d) All of the mentioned

Description : extendible architecture is A. Modular design of a software application that facilitates the integration of new modules B. Showing a universal law or rule to be invalid by providing a counter example C. ... of attributes in a database table that refers to data in another table D. None of these

Last Answer : A. Modular design of a software application that facilitates the integration of new modules

Description : Falsification is A. Modular design of a software application that facilitates the integration of new modules B. Showing a universal law or rule to be invalid by providing a counter example C. A set of attributes in a database table that refers to data in another table D. None of these

Last Answer : B. Showing a universal law or rule to be invalid by providing a counter example

Description : 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 : Automated vehicle is an example of ______. a) Supervised learning b) Unsupervised learning c) Active learning d) Reinforcement learning

Last Answer : a) Supervised learning