BSc CS Sem 5 BSc CS Semester 5 (2020 2021) 2021 Artificial Intelligence Question Paper - Mumbai University | munotes

Sample Question Bank
1]What would be the environment for Part-picking Robot? and bins hand camera arrays and bins
The interdisciplinary field of brings computer
models from Al and experimental techniques from psycology to |Cognitive Cognitive Cognitive Cognitive Cognitive
2|construct theories of human mind. Science Psychology Process Relativism Science
The amount of memory needs to perform the search deals with |Space Complexity Space
If the agent has no sensors at all then the environment is
A combines probability theory with utility
theory, provides a formal and complete framework for Cognitive Decision Boolean Rational Decision
made under uncertainty. Theory Theory Theory Theory Theory
The process of looking for a sequence of actions that reaches Traverse
the goal is called . Merge Find Search Search
The Simple Reflex Agent function is based on condition- action rule condition
Who is the founder of Artificial Intelligence? Arthur Samule} James E. F. Codd McCarthy
Alan Turing developed a technique for determining whether a
computer could or could not demonstrate the artificial Boolean
Intelligence, Presently, this technique is called . Turing Test Algorithm Algebra Logarithm Turing Test
is one that acts to achieve the best outcome. |Agent Agent Agent Agent Agent
If the environment itself does not change with the passage of
time but the agent’s performance score does, then that nondetermini
is . semidynamic |deterministic |episodic semidynamic
12|Clustering is task. Learning Learning t Learning Learning Learning
The Decision Tree Learning algorithm adopts Greedy divide- Greedy divide
13|strategy. votes |stacking bagging and-conquer
An elimination of decision tree nodes that are not clearly
is known as . prunning cutting trimming rooting prunning
The learning problem is called when the
is a number. regression classification |neural net decision tree |regression
are fundamental units of the brain and nervous
A network with all the inputs connected directly to the outputs |Neural Neural Neural neural neural
A learning model that cannot be characterised by bounded |Parametric Nonparametri |Regression Nonparametri
18]of parameters is called . Model c Model Model Decision Tree Model
perceptron is a . Neural algorithm Neural onalgorithm |Neural
The learning problem is called when the
is one of the finite set of values. regression classification |decision tree net classification
are not observable in the data that are available |Hidden Hidden
In Passive Reinforcement Learning, an agent's policy is
EM _ the log likelihood of the data at every
The key concepts of statistical learning is and data,hypothes |probability,da }exploration,ex |data,hypothes
24 . |is ta ploitation is
specifies the probability of reaching state s from Transition Probability Transition
25|state s after doing action a. Bayes Model |Model Model Fixed