Debate and consensus patterns in Agentic AI - Practice Problems & Coding Challenges

Challenge - 5 Problems

🧠 Conceptual

intermediate

What is the main purpose of debate patterns in agentic AI?

In agentic AI systems, multiple agents engage in a debate to reach a conclusion. What is the primary goal of using debate patterns?

A To randomly select one agent's opinion without discussion.

B To allow agents to present opposing views and improve decision quality through argumentation.

C To ensure all agents agree on the first suggestion made.

D To reduce the number of agents involved by eliminating some randomly.

💡 Hint

Think about how debate helps improve decisions by considering different perspectives.

Debate patterns encourage agents to argue different viewpoints, which helps the system find better, well-reasoned answers.

❓ Predict Output

intermediate

Output of a simple consensus function

Consider this Python function that takes a list of agent votes (True or False) and returns the consensus decision (True if majority True, else False). What is the output when votes = [True, False, True, True, False]?

Agentic AI

def consensus(votes):
    true_count = sum(votes)
    return true_count > len(votes) / 2

votes = [True, False, True, True, False]
result = consensus(votes)
print(result)

A Error: unsupported operand

B 3

C True

D False

💡 Hint

Count how many True values are in the list and compare to half the list length.

There are 3 True votes out of 5, which is more than half, so the consensus is True.

❓ Model Choice

advanced

Best model architecture for debate-based agentic AI

You want to build an agentic AI system where multiple agents debate to improve answer quality. Which model architecture is best suited for this?

A A simple linear regression model.

B A single transformer model generating answers without interaction.

C A convolutional neural network for image classification.

D Multiple transformer agents with a shared communication channel for debate.

💡 Hint

Think about how agents can exchange information and argue their points.

Multiple transformer agents communicating allow for interactive debate, improving reasoning and final answers.

❓ Hyperparameter

advanced

Choosing hyperparameters for consensus threshold

In a consensus mechanism, you set a threshold for agreement among agents to accept a decision. What is the effect of setting this threshold too high?

A Decisions may be delayed or never accepted due to strict agreement requirements.

B Decisions are accepted more quickly with less agreement.

C The system ignores agent opinions and picks randomly.

D The system always accepts the first agent's decision.

💡 Hint

Consider what happens if almost all agents must agree before accepting a decision.

A very high threshold means many agents must agree, which can delay or block decisions if consensus is hard to reach.

🔧 Debug

expert

Identify the error in this debate simulation code

What error does this code raise when simulating a debate among agents?

class Agent:
    def __init__(self, name):
        self.name = name
    def argue(self):
        return f"{self.name} argues"

agents = [Agent("A1"), Agent("A2")]
results = [agent.argue for agent in agents]
print(results)

Agentic AI

class Agent:
    def __init__(self, name):
        self.name = name
    def argue(self):
        return f"{self.name} argues"

agents = [Agent("A1"), Agent("A2")]
results = [agent.argue for agent in agents]
print(results)

A No error, prints ['A1 argues', 'A2 argues']

B SyntaxError: invalid syntax

C TypeError: 'method' object is not callable

D NameError: name 'agent' is not defined

💡 Hint

Check how the method is called inside the list comprehension.

The code does not call the argue method (missing parentheses), so results is a list of method objects. Printing results shows method objects, no error occurs.