Why multiple agents solve complex problems in Agentic AI - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a list of agents.

Agentic AI

agents = [[1] for _ in range(5)]

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

Aagent

BAgent()

C5

Drange(5)

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'agent' instead of 'Agent()' creates a list of the same reference.

The code creates 5 new Agent objects in a list using a list comprehension.

2fill in blank

medium

Complete the code to have each agent perform a task.

Agentic AI

for agent in agents:
    agent.[1]()

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

Arun

Bexecute

Cstart

Dperform_task

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'run' or 'start' which may not be defined methods.

The method perform_task() is called on each agent to make it do its job.

3fill in blank

hard

Fix the error in the code to collect results from agents.

Agentic AI

results = [agent.[1] for agent in agents]

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

Aget_result()

Bresult

Cresult()

DgetResult

Attempts:

3 left

💡 Hint

Common Mistakes

Forgetting parentheses causes a list of method references, not results.

The method get_result() must be called with parentheses to get each agent's output.

4fill in blank

hard

Fill both blanks to combine agent results and check if all succeeded.

Agentic AI

combined = sum(results)
all_success = all(result [1] [2] 0 for result in results)

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

A>

B==

C>=

D<

Attempts:

3 left

💡 Hint

Common Mistakes

Using '==' would only check for exact zero, not success range.

We check if all results are greater than or equal to zero to confirm success.

5fill in blank

hard

Fill all three blanks to create a dictionary mapping agent IDs to their results if result is positive.

Agentic AI

agent_results = {agent.id: result for agent, result in zip(agents, results) if result [1] [2] 0 and agent.[3]

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

A>

B>=

Cis_active

Dis_ready

Attempts:

3 left

💡 Hint

Common Mistakes

Using incorrect attribute names or wrong comparison operators.

The dictionary comprehension filters results greater than zero and only includes agents that are active.

Practice

1. Why do multiple agents working together solve complex problems better than a single agent?

easy

A. Because agents do not communicate and work independently without sharing.

B. Because one agent can do all the work alone without help.

C. Because they divide the work and share knowledge to find solutions faster.

D. Because multiple agents always produce the same results as one agent.

Solution

1. Step 1: Understand agent collaboration

   Multiple agents split a big problem into smaller parts and work on them separately.

2. Step 2: Recognize knowledge sharing

   Agents share what they learn, combining their results for a better solution.

3. Final Answer:

   Because they divide the work and share knowledge to find solutions faster. -> Option C

4. Quick Check:

   Multiple agents collaborate = better solutions [OK]

Hint: Think teamwork: many hands make light work [OK]

Common Mistakes:

• Assuming one agent can solve everything alone
• Ignoring the benefit of sharing knowledge
• Thinking agents work without communication

2. Which of the following is the correct way to describe multiple agents working together?

easy

A. Agents divide tasks and communicate their findings.

B. Agents compete to solve the same task alone.

C. Agents work independently without sharing any information.

D. Agents ignore each other and solve unrelated problems.

Solution

1. Step 1: Identify correct teamwork behavior

   Multiple agents divide tasks and share results to solve complex problems.

2. Step 2: Eliminate incorrect options

   Options A, B, and D describe no communication or competition, which is not teamwork.

3. Final Answer:

   Agents divide tasks and communicate their findings. -> Option A

4. Quick Check:

   Task division + communication = teamwork [OK]

Hint: Look for teamwork and communication keywords [OK]

Common Mistakes:

• Choosing options that say agents work alone
• Confusing competition with collaboration
• Ignoring the need for communication

3. Consider this Python-like pseudocode for two agents working on parts of a problem:

agent1_result = 5
agent2_result = 7
combined_result = agent1_result + agent2_result
print(combined_result)

What will be the output?

medium

A. 57

B. 12

C. Error

D. None

Solution

1. Step 1: Understand variable values

   agent1_result is 5 and agent2_result is 7, both numbers.

2. Step 2: Calculate combined_result

   Adding 5 + 7 equals 12, so print outputs 12.

3. Final Answer:

   12 -> Option B

4. Quick Check:

   5 + 7 = 12 [OK]

Hint: Add numbers, not strings, to get sum [OK]

Common Mistakes:

• Treating numbers as strings and concatenating
• Expecting an error from simple addition
• Ignoring the print output

4. This code tries to combine results from two agents but has an error:

agent1 = 10
agent2 = 20
combined = agent1 + agent2_result
print(combined)

What is the error and how to fix it?

medium

A. Variable 'agent2_result' is undefined; change to 'agent2'.

B. Syntax error due to missing colon.

C. Cannot add integers; convert to strings first.

D. Print statement is missing parentheses.

Solution

1. Step 1: Identify variable names

   Code uses 'agent2_result' but only 'agent2' is defined.

2. Step 2: Fix variable name

   Replace 'agent2_result' with 'agent2' to fix the NameError.

3. Final Answer:

   Variable 'agent2_result' is undefined; change to 'agent2'. -> Option A

4. Quick Check:

   Correct variable names avoid errors [OK]

Hint: Check variable names carefully for typos [OK]

Common Mistakes:

• Assuming syntax error without checking variables
• Thinking addition of integers causes error
• Ignoring exact error message

5. In a system with three agents solving parts of a complex task, agent A finds data patterns, agent B cleans data, and agent C builds a model. Why is this multi-agent approach better than one agent doing all steps?

hard

A. Because one agent would do all steps faster without errors.

B. Because splitting tasks causes confusion and slows down work.

C. Because agents do not need to share results to succeed.

D. Because each agent specializes, speeding up the process and improving quality.

Solution

1. Step 1: Understand specialization benefits

   Each agent focuses on one task, becoming better and faster at it.

2. Step 2: Recognize teamwork advantage

   Sharing results lets agents build on each other's work for a better final model.

3. Step 3: Compare with single agent approach

   One agent doing all tasks may be slower and less effective due to multitasking.

4. Final Answer:

   Because each agent specializes, speeding up the process and improving quality. -> Option D

5. Quick Check:

   Specialization + teamwork = better results [OK]

Hint: Think specialists working together beat one multitasker [OK]

Common Mistakes:

• Believing one agent is always faster
• Ignoring the need for communication
• Thinking splitting tasks causes delays