Artificial Intelligence And Robotics Set 4
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This set of Artificial Intelligence and Robotics AIR Multiple Choice Questions & Answers (MCQs) focuses on Artificial Intelligence And Robotics Set 4
Q1 | Which is not problem in Hill climing?
- plateau
- ridges
- local maximum
- landscape
Q2 | Tabu search is designed __________________________
- as it does not follow aspiration criteria
- to escape the trap of local optimality.
- to unrecord forbidden moves, which are referred to as tabu moves .
- all of the above
Q3 | Production/Rule looks like________________
- pattern-->data
- action-->data
- pattern-->action
- none of the above
Q4 | How can we convert AO graph with mixed nodes into graph with pure AND and OR nodes?
- by traversing multiple node
- by deleting one of the node
- by addition of extra node
- none of the above
Q5 | Arc consistency in AO graph is concernd with ____________________________________
- nodes
- finding consistent values for pairs of variables.
- unary constraint
- all of the above
Q6 | A planning problem P in BSSP is defined as a _____________
- triple (s, g, o)
- triple (s1, s2, o)
- triple (g1, g, o)
- none of the above
Q7 | Plan representation in Plan Space Planning is done with__ -----------links
- binding links
- ordering links and casual link
- contigent link
- head step
Q8 | What is true aboout Iterative Deepening DFS?
- it does not perform dfs in a bfs fashion.
- it is the preferred informed search method
- it’s a depth first search, but it does it one level at a time, gradually increasing the limit, until a goal is found.
- is a depth-first search with a fixed depth limit l
Q9 | What is the main advantage of backward state-space search?
- cost
- actions
- relevant actions
- all of the mentioned
Q10 | Backward State Space Planning (BSSP)_______________________________
- simply explores the set of all future states in possible order
- start searching backwards from the goal
- leads to huge search space
- has no sense of direction
Q11 | In Backward State Space Planning ,regress(A,G) that returns ______________________________
- the regressed goal over action a when applied to goal g.
- the goal state over action a when applied to goal g.
- the initial state over action a when applied to goal g.
- both a & b
Q12 | What is true about Backward State Space Planning?
- goal states are often incompletely specified.
- expresses only what is desired in the final state, rather than a complete description of the final state.
- it uses regression
- all of the above
Q13 | effects⁺ (a) in Forward State Space Planning denotes ___________________
- denotes the set of negative effects of action a
- denotes the set of neutral effects of action a
- denotes the set of positive effects of action a
- none of the above
Q14 | In Forward State Space Planning , Progress ( A, S) function returns ___________________
- the successor state s when action a is applied to state s.
- the predecessor state s when action a is applied to state s.
- both a & b
- none of the above
Q15 | What are the drawbacks of Forward State Space Planning?
- fssp has very huge search space
- it includes the actions that have nothing go do with achieving the goal
- regression is used in forward state space planning
- both a & b
Q16 | What arcs represents in AO Graph?
- subproblem to be solved individually
- solution
- path
- sequence of actions
Q17 | Which are the first AI applications of AO graph?
- saint
- xcon
- dendral
- both a and c
Q18 | What is Hyper-Edge in AO Graph?
- many edges together can be hyber edge
- those are and edges only
- both 1 and 2
- none of the above
Q19 | What cost is assumed for arc while solving AO* progress example?
- 0
- 1
- 2
- 3
Q20 | What is the heuristic cost of SOLVED nodes in AO* example?
- 0
- 1
- 2
- 3
Q21 | What is used to lable primitive problems in AO problem?
- unvisited
- unsolved
- solved
- visited