CS 7638 FINAL EXAM QUESTIONS WITH CORRECT ANSWERS LATEST UPDATE 2026
Kalman Filters are unimodal (True/False) - Answers True
Kalman Filters have exponential complexity (True/False) - Answers False
Histogram Filters are multimodal (True/False) - Answers True
Histogram Filters have exponential complexity (True/False) - Answers True
Particle Filters are unimodal (True/False) - Answers False
Particle Filters have exponential complexity (True/False) - Answers True
BFS is continuous (True/False) - Answers False
BFS is guaranteed to find the optimal path (True/False) - Answers True
A* is continuous (True/False) - Answers False
A* is guaranteed to find the optimal path (True/False) - Answers True
Dynamic Programming (Dijkstra) is continuous (True/False) - Answers False
Dynamic Programming (Dijkstra) is guaranteed to find the optimal path (True/False) - Answers True
Path Smoothing is continuous (True/False) - Answers True
Path Smoothing is guaranteed to find the optimal path (True/False) - Answers False
Path finding algorithm that only works for unweighted graphs (BFS/Dijkstra/A*) - Answers BFS
Path finding algorithm that gives the optimal path between any two nodes, not just a source and a
destination (BFS/Dijkstra/A*) - Answers Dijkstra
Path finding algorithm that uses a heuristic to improve expected efficiency (BFS/Dijkstra/A*) -
Answers A*
A heuristic used in A* must be "admissible" in order to return the optimal path (True/False) - Answers
True
PID term that minimizes error (Proportional, Integral, Derivative) - Answers Proportional
PID term that avoids overshoot (Proportional, Integral, Derivative) - Answers Derivative
PID term that compensates for drift/eliminates steady state error (Proportional, Integral, Derivative) -
Answers Integral
When developing a heuristic for A*, the heuristic is admissible when:
A - The heuristic is less than the cost to the goal
B - The heuristic is more than the cost to the goal
C - The heuristic is equal to the cost to the goal
D - Both A and C
E - Both B and C - Answers D
In GraphSLAM, landmarks must be distinguishable (True/False) - Answers True
In a Particle Filter, the particle will the highest weight is always resampled (True/False) - Answers
False
A probability distribution must be normalized before being used in a localization calculation
(True/False) - Answers False
Name this term: A mapping from all states to the optimal action to take from that state in order to
reach a goal - Answers Policy
When navigating from a single starting point to a single ending point, which algorithm is more
efficient (A*/Dijkstra) - Answers A*
Kalman Filters are unimodal (True/False) - Answers True
Kalman Filters have exponential complexity (True/False) - Answers False
Histogram Filters are multimodal (True/False) - Answers True
Histogram Filters have exponential complexity (True/False) - Answers True
Particle Filters are unimodal (True/False) - Answers False
Particle Filters have exponential complexity (True/False) - Answers True
BFS is continuous (True/False) - Answers False
BFS is guaranteed to find the optimal path (True/False) - Answers True
A* is continuous (True/False) - Answers False
A* is guaranteed to find the optimal path (True/False) - Answers True
Dynamic Programming (Dijkstra) is continuous (True/False) - Answers False
Dynamic Programming (Dijkstra) is guaranteed to find the optimal path (True/False) - Answers True
Path Smoothing is continuous (True/False) - Answers True
Path Smoothing is guaranteed to find the optimal path (True/False) - Answers False
Path finding algorithm that only works for unweighted graphs (BFS/Dijkstra/A*) - Answers BFS
Path finding algorithm that gives the optimal path between any two nodes, not just a source and a
destination (BFS/Dijkstra/A*) - Answers Dijkstra
Path finding algorithm that uses a heuristic to improve expected efficiency (BFS/Dijkstra/A*) -
Answers A*
A heuristic used in A* must be "admissible" in order to return the optimal path (True/False) - Answers
True
PID term that minimizes error (Proportional, Integral, Derivative) - Answers Proportional
PID term that avoids overshoot (Proportional, Integral, Derivative) - Answers Derivative
PID term that compensates for drift/eliminates steady state error (Proportional, Integral, Derivative) -
Answers Integral
When developing a heuristic for A*, the heuristic is admissible when:
A - The heuristic is less than the cost to the goal
B - The heuristic is more than the cost to the goal
C - The heuristic is equal to the cost to the goal
D - Both A and C
E - Both B and C - Answers D
In GraphSLAM, landmarks must be distinguishable (True/False) - Answers True
In a Particle Filter, the particle will the highest weight is always resampled (True/False) - Answers
False
A probability distribution must be normalized before being used in a localization calculation
(True/False) - Answers False
Name this term: A mapping from all states to the optimal action to take from that state in order to
reach a goal - Answers Policy
When navigating from a single starting point to a single ending point, which algorithm is more
efficient (A*/Dijkstra) - Answers A*
