What is an AI agent in Agentic AI - Interactive Quiz & Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to define an AI agent that takes actions based on observations.

Agentic AI

class AIAgent:
    def __init__(self):
        pass

    def act(self, observation):
        return [1]

Drag options to blanks, or click blank then click option'

ANone

Bself

Cobservation

Daction

Attempts:

3 left

💡 Hint

Common Mistakes

Returning the observation instead of an action.

Returning self which is not an action.

The act method should return an action. Returning None means no action is taken yet.

2fill in blank

medium

Complete the code to initialize the AI agent's internal state.

Agentic AI

class AIAgent:
    def __init__(self):
        self.state = [1]

Drag options to blanks, or click blank then click option'

A{}

B[]

CNone

D0

Attempts:

3 left

💡 Hint

Common Mistakes

Using a list [] which is less descriptive for state.

Setting state to None which means no state.

The internal state is best represented as an empty dictionary {} to store key-value pairs.

3fill in blank

hard

Fix the error in the method that updates the agent's state with new observations.

Agentic AI

def update_state(self, observation):
    self.state.update([1])

Drag options to blanks, or click blank then click option'

Aself

BNone

Cstate

Dobservation

Attempts:

3 left

💡 Hint

Common Mistakes

Passing self or None which causes errors.

Passing state which is not defined in this scope.

The update method requires a dictionary argument, so passing observation (assumed to be a dict) updates the state correctly.

4fill in blank

hard

Fill both blanks to create a method that decides an action based on the agent's state.

Agentic AI

def decide_action(self):
    if 'goal' in self.state and self.state['goal'] [1] 0:
        return 'move_towards_goal'
    else:
        return [2]

Drag options to blanks, or click blank then click option'

A>

B'idle'

C<

D'wait'

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' instead of '>' which reverses the logic.

Returning 'wait' instead of 'idle' which is not the expected action.

The agent checks if the goal value is greater than zero to decide to move. Otherwise, it returns 'idle' to do nothing.

5fill in blank

hard

Fill all three blanks to implement a simple AI agent loop that updates state, decides action, and acts.

Agentic AI

def run_agent(agent, observation):
    agent.state.update([1])
    action = agent.[2]()
    return agent.[3](action)

Drag options to blanks, or click blank then click option'

Aobservation

Bdecide_action

Cact

Dupdate_state

Attempts:

3 left

💡 Hint

Common Mistakes

Calling the wrong methods in the wrong order.

Passing wrong arguments to methods.

The agent updates its state with the observation, decides an action, then acts on that action.