Quiz on LLM-based Agents

Quiz on LLM-based Agents

Professional Development

10 Qs

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Quiz on LLM-based Agents

Quiz on LLM-based Agents

Assessment

Quiz

Computers

Professional Development

Practice Problem

Hard

Created by

Сергей Тращенков

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10 questions

Show all answers

1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the primary function of the brain module in an LLM-based agent?

Influencing the surroundings

Executing actions using tools

Memorizing, thinking, and decision-making

Perceiving and processing multimodal information

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which property of an agent refers to its ability to respond rapidly to immediate changes and stimuli in its environment?

Social ability

Autonomy

Reactivity

Pro-activeness

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the main advantage of using large language models (LLMs) as the primary component of an agent's brain?

Ability to generate human-like text and engage in conversations

Capacity to autonomously formulate plans and execute them

Enhanced task performance through social behaviors

Capability to exhibit reasoning and planning abilities

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which approach in AI research focuses on the interaction between an agent and its environment, emphasizing quick and real-time responses?

Agents with transfer learning and meta learning

Reinforcement learning-based agents

Reactive agents

Symbolic agents

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the primary role of the perception module in an LLM-based agent?

Executing actions using tools

Influencing the surroundings

Perceiving and processing multimodal information

Memorizing, thinking, and decision-making

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which property of an agent refers to its capacity to interact with other agents, including humans, through some kind of agent-communication language?

Autonomy

Reactivity

Pro-activeness

Social ability

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the main limitation of reinforcement learning-based agents?

Lack of complex higher-level decision-making and planning capabilities

Inability to exhibit goal-oriented actions

Difficulty in perceiving and processing multimodal information

Long training times and low sample efficiency

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