
Informed Search: Consider the following graph where nodes are states,
arcs are operators labeled with costs, values to the right of nodes are
their heuristic evaluations, A is the initial state, and G
is the goal state:
In (a)(d), you will give the order in which nodes are goaltested according
to different informed or heuristic search strategies employing
different ways of avoiding repeated states. List the order of node goaltesting
until the search terminates or 18 nodes have been listed. Ties in node
ordering are broken alphabetically by state label.

Greedy, no repeats

A/A*, generate all

IDA/IDA*, no cycles

Is our heuristic evaluation function h admissible? Why or why not?

Show why f is not monotonic.

Modify f according to the pathmax equation.

Multiple choice:

The drawback of A* is that

it takes more time than depthfirst search

it takes exponential space (in the depth of the goal)

it may be difficult to find a (useful) admissible heuristic function.

both ii,iii

all of i,ii,iii

Select the most space conserving search of those mentioned below:

A* search with h(n) = 0 for all n

iterativedeepening search

breadthfirst search

A* search with an admissible heuristic

One of the problems hillclimbing does not have is:

the localminima problem

the plateau problem

the horizon problem

the ridge problem

TripleCross Challenge #2:

Create an admissible heuristic h for TripleCross. Explain
why h is admissible.

Program IDA* and compare its performance to iterativedeepending depthfirst
search.

Use a weighted evaluation function and show how performance varies
for different weights.