Estd: 1986
DEPARTMENT OF ARTIFICIAL INTELLIGENCE & MACHINE
LEARNING
Tutorial - 1
SUBJECT TITLE ADVANCED AI ML
SUBJECT TYPE THEORY
SUBJECT CODE 21AI71
ACADEMIC YEAR 2024-25 (odd semester) Batch 2021-2025
SCHEME CBCS 2021
SEMESTER VII sem
FACULTY NAME and NAGARJUNA G R A, Assistant Professor
DESIGNATION
DATE of ISSUED 17-10-2024
Q. Questions Level COs
No.
1 Define Agent, Explain the concept of agent with an example and neat diagram. L1
CO1
2 Explain with a neat diagram Utility-based agents and concept of learning agents. L2 CO1
3 Categorize the various types of Agent Architectures and explain any two. L3 CO1
Categorize the various Properties of task environments and explain them with an L3
4 CO1
example.
5 Explain the optimal decisions in games with an example. L2 CO1
6 Explain the elements involved in the game. L2
CO1
7 Explain the concept of inference using full joint distributions. L2
CO2
8 Explain the concept agents acting under uncertainty. L2
CO2
9 Explain the probability model and language of propositions in probability assertions. L2
CO2
Illustrate with a neat diagram how agents interact with environments through sensors and L2
10 actuators. CO1
11 Explain knowledge-based agents. Write a generic knowledge-based agent. L2
CO1
12 Discuss Wumpus world. Give PEAS description L2
CO2
13 Explain the concept of independence and Bayes’ rule and its use in uncertainty. L2
CO2
14 Discuss the concept of percepts and actions in the agent-environment interaction. L2
CO1
15 Provide examples of intelligent agents in real-world applications. L2
CO1
16 Explain the interaction between agents and their environments in the context of AI L2
CO2
17 Explore the relationship between rationality and decision-making in AI systems. L2
CO2
Analyze how different types of environments can affect the performance of intelligent L3
18 CO1
agents.
Differentiate between simple reflex agents, model-based agents, goal-based agents, and L3
19 CO1
utility-based agents.
20 Define rationality in the context of intelligent agents. L2
CO1
Sign of the faculty HOD
NAGARJUNA G R
