There are five graduate CS classes and three instructors who will be
teaching these classes. An instructor can only teach one class at a time.
The classes are:
Algorithms: meets from
Intro to AI: meets from 8:30
Databases: meets from 9:00
Operating Systems: meets from 9:00
Machine Learning: meets from 9:30
and the instructors are:
who is available to teach Classes 3 and 4.
Professor B, who is available to teach Classes 2, 3, 4, and 5.
Professor C, who is available to teach Classes 1, 2, 3, 4, 5.
Formulate this as a CSP problem in which there is one variable per
e the variables
and their domains, and the constraints.
Draw the constraint graph associated with your CSP.
Show the domains of the variables after running arc
initial graph (after enforcing any unary constraints.)
one solution to this CSP.
Queen, set up as a constraint satisfaction problem, has the
intermediate stage as in
the following figure:
Using an "F," mark the positions in the last four columns that will be
as possible positions for a queen by
Using an "A," mark the positions in the last four columns that are
already marked with an "F" and that will be
. (Use this process repeatedly until no
Hence give a solution to this problem.
Consider the map below which is not drawn to scale. The nodes
denote cities while the edges denote
the latter labelled by a number to denote
Using A* Search, work out the optimal route from city A to city G.
The straight line distances (SLD) to city G from each city are given
rovide the search tree for your solution, showing the order in which
the nodes were expanded and
cost at each
node. Finally, state
the route you would take and the cost of that route.
Consider the following state space graph where the bi
represent all the legal successors of a node. The cost of each
successor function is given by the number on the arc. The value of a
heuristic evaluation function h, if computed at a sta
te, is shown
alongside each node. The initial and goal states are S and G
When a node is expanded, its children are put in a QUEUE data
structure consisting of all the fringe nodes sorted by values of an
evaluation function. In case of ties of the latter, the order in the
QUEUE will be decided
by alphabetical order. A child node will not
be generated if that same node is an ancestor of the current node
in the search tree.
What would be the order of node expansion if the following search
algorithms are used? For both cases, show at each step wh
are in the QUEUE.