BSc CS Sem 5 2023 2024 2024 ARTIFICIAL INTELLIGENCE Question Paper - Mumbai University | munotes

Questions asked in this paper

• 2) Figures to the right indicate marks

1. Q3 Illustrations, in-depth answers and diagrams will be appreciated
2. Q4 Mixing of sub-questions is not allowed
3. Q1 Attempt ANY FOUR from the following: (20M)
   • (a) What is PEAS? Give a PEAS description for playing a tennis match and vacuum
   • (b) Define AI? Explain any 2 foundations of AI
   • (c) Explain the 8-Queens Problem and write the States, Initial state, Actions, Transition Model, Goal state & Path cost to formulate it
   • (d) Explain Depth First Strategy along with pseudocode
   • (e) Write a short note on model based agent
   • (f) Find the optimal path & path cost for the following graph using A* search algorithm. (S is a Start state & G is a Goal State)
4. Q2 Attempt ANY FOUR from the following: (20M)
   • (a) Describe knowledge representation. Explain frame representation technique of knowledge representation in detail
   • (b) Write a note on Multilayer Feed Forward Neural Network
   • (c) Explain the concept of Overfitting and Underfitting of model
   • (d) What is Regression? Explain Simple Linear Regression with example
   • (e) Define Ensemble Learning. Explain Boosting technique in detail
   • (f) Explain KNN classifier with example
5. Q3 Attempt ANY FOUR from the following: (20M)
   • (a) Write a short note on Q learning
   • (b) Differentiate between reinforcement and unsupervised learning
   • (c) For the given transaction dataset Calculate the following :
   • (d) Explain Hidden Markov Model in detail
   • (e) What is Clustering? Explain with example
   • (f) Write a short note on association rule mining Attempt ANY FIVE from the following: (15M)
   • (a) Explain Turing Test Approach in AI
   • (b) Explain Deterministic vs Stochastic Task Environment with suitable example
   • (c) Write a note on Active Reinforcement learning
   • (d) Explain Bellman Equation in detail
   • (e) What is the role of Reasoning in AI?
   • (f) Explain the concept of gradient descent

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