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In agentic AI systems, multiple agents engage in a debate to reach a conclusion. What is the primary goal of using debate patterns?
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.
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]?
def consensus(votes): true_count = sum(votes) return true_count > len(votes) / 2 votes = [True, False, True, True, False] result = consensus(votes) print(result)
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.
You want to build an agentic AI system where multiple agents debate to improve answer quality. Which model architecture is best suited for this?
Think about how agents can exchange information and argue their points.
Multiple transformer agents communicating allow for interactive debate, improving reasoning and final answers.
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?
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.
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)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)
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.