Question

Question 1

1. A finite-state machine (FSM) can serve as a useful model of a continuous (all its variables / attributes have real number values with infinite range and precision) environment. Yes or no?

   Yes

   No

    
   

     

Question 2

1. Breadth-first and depth-first tree searches always start the search process at the root of the tree. Yes or no?

   Yes

   No

   
   

     

Question 3

1. Consider a single-agent system where some agent A can travel to every place on the surface of the Earth (environment). 

   Every place (environment state) on Earth can be defined by its latitude and longitude. Now imagine that both latitude and longitude values are always expressed with real numbers [having infinite precision (~ infinite number of decimal places)].

   What does it tell you about the environment (which statement is supported by the information above)?

   		The environment is continuous.
   		The environment is episodic.
   		The environment is known to the agent.
   		The environment is non-deterministic.

    
   

     

Question 4

1. A recursive solution to a problem is ALWAYS going to be more efficient (in terms of space and time complexity) than its iterative equivalent. True or False?

   True

   False

    
   

Question 5

1. Google provides 41.8781° N, 87.6298° W as latitude and longitude of Chicago.

   Consider a single-agent system where some agent A can travel to every place on the surface of the Earth (environment). In this arrangement, "Chicago" would be a state label / name and that "Chicago" state can be described by two variables, longitude and latitude (with specific values shown above | you can ignore the fact that moving a bit west or north of that point is still Chicago).

   Agent A perceives longitude and latitude and stores/uses both as its internal environment state representation. What kind of state representation would that be?

   		neither
   		atomic
   		factored
   		structured

    
   

     

Question 6

1. Building entire search tree prior to searching can be impossible for some state spaces. True or false?

   True

   False

    
   

     

Question 7

1. A search algorithm that will always find a solution (if it exists) is .... .

   		perfect
   		proper
   		optimal
   		complete

    
   

     

Question 8

1. A solution to a state space search is ... .

   		the cost of getting from the initial to the goal state
   		a path between initial and goal states
   		a "found" or "not found" message
   		the list of goal states (if more than one)

    
   

     

Question 9

1. A node in a state space search tree represents a state (let's call it X). The number of possible branches "going out" of X / children nodes of x ... .

   		is always fixed
   		is related to the number of possible agent actions when at state X
   		depends on whether you use depth-first search or breadth-first search
   		is zero

    
   

Question 10

1. NOT handling repeated states during the state space search can lead to?

   		Reducing state space size.
   		Finding the solution faster.
   		Infinite search process.
   		Reducing the amount of resources used.

    

Answer 1

1. no

a finite-state machine (FSM) is not a suitable model for a continuous environment where all variables have real number values with infinite range and precision. FSMs are designed to represent and model systems with a finite number of discrete states and transitions between these states. They work well for systems with a limited number of distinct states, such as digital logic circuits, software control flow, or other systems with discrete events or decision points.