Machine-translated by Google. Questions are authored in English.
Top

Planning Questions and Answers

1.

Which of the following is not a property of planning graph ?

Exam Year(s)

MH SET - 2019, SET Exam - 2019,

Answer: B

The statement that is not a property is Actions decrease monotonically.

In a planning graph (as in GraphPlan), literals increase monotonically: once a literal appears at a level, it persists through no-op actions to all later levels. Actions increase monotonically too: once an action's preconditions appear, they remain, so the action stays available. Mutexes decrease monotonically, because if two items are mutually exclusive at a level they were also mutex at every earlier level.

Since literals and actions only grow and mutexes only shrink, the graph eventually levels off when two consecutive levels are identical. So actions do not decrease.

Please log in or register to report this question.

Discuss in Forum
2.

Which of the following is not true for STRIPS language used for planning ?

Exam Year(s)

MH SET - 2020, SET Exam - 2020,

Answer: C

The statement not true of STRIPS is It uses open world assumption.

STRIPS uses the closed world assumption: any condition not mentioned in a state is taken to be false. It is ADL (Action Description Language) that adopts the open world assumption.

The other statements are true of STRIPS: states contain only positive literals, goals and effects are conjunctions, and there is no built-in support for equality or types, which ADL adds.

Please log in or register to report this question.

Discuss in Forum
3.

Sensorless planning is also known as :

Exam Year(s)

MH SET - 2021, SET Exam - 2021,

Answer: A

Sensorless planning is also known as Conformant planning.

In sensorless (conformant) planning the agent cannot observe the world, so it must find a fixed sequence of actions that reaches the goal whatever the initial state or the outcomes of its actions turn out to be. It reasons over belief states, the sets of states it might be in.

Conditional or contingency planning is the opposite case: the agent can sense, and the plan branches on what it observes. Continuous planning keeps revising the plan as the world changes while it executes.

Please log in or register to report this question.

Discuss in Forum
4.

Forward state space search is also known as :

Exam Year(s)

MH SET - 2023, SET Exam - 2023,

Answer: B

Forward state space search is also known as progression planning.

A forward planner starts from the initial state and applies actions whose preconditions are satisfied, progressing through successor states until it reaches a state that satisfies the goal.

Regression planning is the opposite, backward search: it starts from the goal and regresses through actions to subgoals until it reaches the initial state. Contingency planning prepares plans with branches for different observations in uncertain environments, and 'consistency planning' is not a standard term.

Please log in or register to report this question.

Discuss in Forum
5.

The mean-end analysis process centers around the detection of differences between the current state and goal state. Once such a difference is isolated, an operator that can reduce the difference must be found. But perhaps that operator can not be applied to the current state. So a sub-problem of getting to a state in which it can be applied is set up. The kind of backward chaining in which operators are selected and then sub goals are set up to establish the precondition of operators is called

Exam Year(s)

UGC NET - 2013,

Answer: C

The kind of backward chaining in which operators are selected and sub goals are set up to establish the preconditions of the operators is called operator subgoaling. In means-end analysis, once a difference is found, an operator that reduces it is chosen, and if it cannot yet be applied, the aim of making its preconditions true becomes a sub problem.

Goal stack planning and backward planning are different planning methods, and operator overloading is a programming language feature.

Please log in or register to report this question.

Discuss in Forum
6.

The Blocks World Problem in Artificial Intelligence is normally discussed to explain a _______

Exam Year(s)

UGC NET - 2013,

Answer: B

The blocks world problem is normally discussed to explain a planning system. In it a robot arm has to rearrange blocks on a table using operators such as pick up, put down and stack, and the aim is to find a sequence of actions from the start to the goal arrangement, which is a planning task.

It is solved with search, but the problem is used as the standard planning example, not to teach search techniques as such. It is not a constraint satisfaction problem and it is not a question of building a knowledge base, so the other options are wrong.

Please log in or register to report this question.

Discuss in Forum
7.

Means-Ends Analysis process centres around the detection of difference between the current state and the goal state. Once such a difference is found, then to reduce the difference one applies ______

Exam Year(s)

UGC NET - 2013,

Answer: D

In means-ends analysis, once a difference between the current state and the goal state is found, one applies an operator that can reduce the difference. If the operator cannot be applied at once, a subgoal is set to meet its conditions, and the process repeats.

Forward, backward and bidirectional search describe the direction in which a search is carried out. Means-ends analysis chooses operators on the basis of the difference, so these options do not describe the step.

Please log in or register to report this question.

Discuss in Forum
8.

STRIPS addresses the problem of efficiently representing and implementation of a planner. It is not related to which one of the following ?

Exam Year(s)

UGC NET - 2014,

Answer: C

STRIPS is not related to NLP.

STRIPS was developed at SRI to plan the actions of the robot SHAKEY. It is a planner and not a natural language processing system.

SHAKEY and SRI are both related to it, so options A and B are wrong, and D says none applies. The name STRIPS stands for Stanford Research Institute Problem Solver. It was built as the planner for the SHAKEY robot, so both of those names are related to it, whereas natural language processing is a separate area of artificial intelligence.

Please log in or register to report this question.

Discuss in Forum
9.

How is a state represented in classical planning?

Answer: A

A state is a set of fluents, and everything not listed is false by the closed world assumption, which is a factored representation and is exactly what lets a planner reason about actions without enumerating states. Atomic tokens would hide the structure, distributions belong to probabilistic planning and action sequences are plans rather than states. Choosing a representation in which an action's effect can be described locally is what makes planning different from ordinary search.

Please log in or register to report this question.

Discuss in Forum
10.

Why does classical planning adopt the closed world assumption?

Answer: B

Listing only what is true keeps a state description short, since the alternative would be to record the truth or falsity of every atom. It is appropriate because a planner's model of the world is complete by construction. Solvability, uncertainty and goal testing are unaffected. An assumption adopted because the domain genuinely satisfies it, rather than for convenience, is the legitimate use of the closed world reading.

Please log in or register to report this question.

Discuss in Forum
Loading…

Topics

Other Subjects

Tags: Planning Questions and Answers || Planning MCQ Questions and Answers || Planning GK Questions and Answers || Planning GK MCQ Questions || Planning Multiple Choice Questions and Answers || Planning GK || GK on Planning || Artificial Intelligence Questions and Answers || Artificial Intelligence MCQ Questions and Answers || Artificial Intelligence GK Questions and Answers || GK on Artificial Intelligence

About Us

ExamsRepo

Copyright © 2026 ExamsRepo . All Rights Reserved . With