PESIT Bangalore South Campus Hosur road, 1km before Electronic City, Bengaluru -100 Department of Computer Science and Engineering

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1 INTERNAL ASSESSMENT TEST 1 Date : Max Marks: 50 Subject & Code : Artificial Intelligence / CS764 Sections : A, B and C Name of faculty: Ms.Sudeepa (A & C)/Ms.Pooja (B) Time : 11.30am 1:00pm Note: Answer any five full questions. What is artificial Intelligence and its four approaches? Explain the interaction of agents and environment with the help of a vaccum cleaner world. AI is the study of how to make computers do things which at the moment people do better. Examples: Speech recognition, Smell, Face, Object, Intuition, Inferencing, Learning new skills, Decision making, Abstract thinking, solving mathematical problems etc.

2 a. Write short notes on the following with examples a) Rationality and rational agents Rational Agent - A rational agent should strive to "do the right thing", based on what it can perceive and the actions it can perform. The right action is the one that will cause the agent to be most successful. Performance measure: An objective criterion for measuring the success of an agent's behavior, That is how the Agent s behavior can be measured. E.g., performance measure of a vacuum-cleaner agent could be amount of dirt cleaned up, amount of time taken, amount of electricity consumed, amount of noise generated, etc. Rationality Performance measure that defines the criterion of success Agent s prior knowledge of environment Actions that agent can perform Agent s percept sequence to date Rational Agent: For each possible percept sequence, a rational agent should select an action that is

3 b expected to maximize its performance measure, given the evidence provided by the percept sequence and whatever built-in knowledge the agent has. PEAS description of different agent types Consider, e.g., the task of designing an Automated Taxi Driver (can chk proceedings of conf on Intelligent Transportation System) Performance measure: Safe, fast, legal, comfortable trip, maximize profits Environment: Roads, other traffic, pedestrians, customers Actuators: Steering wheel, accelerator, brake, signal, horn Sensors: Cameras, sonar ( to detect distances to other cars or anything else), speedometer, GPS, odometer, engine sensors, keyboard( or a microphone for passenger to request a destination) Agent: Medical diagnosis system Performance measure: Healthy patient, minimize costs, lawsuits Environment: Patient, hospital, staff Actuators: Screen display (questions, tests, diagnoses, treatments, referrals) Sensors: Keyboard (entry of symptoms, findings, patient's answers) What is the structure of Agents and explain various types of agents with the agent programs. Four basic types in order of increasing generality: Simple reflex agents Model-based reflex agents Goal-based agents Utility-based agents Detailed of all these.. Formulate the problem, operators and Perform a state space search for a water jug problem which is as follows:- You are given two jugs, a 4-litre one and a 3-litre one. Neither has any measuring markers on it. There is a pump that can be used to fill the jugs with water. How can you get exactly 2 litres of water into 4-litre jug. Initial state:

4 The buckets are empty Represented by the tuple ( 0 0 ) Goal state: One of the buckets has two gallons of water in it Represented by either ( x 2 ) or ( 2 x ) Path cost: 1 per unit step

5 USN 1 P E. What are uninformed search strategies? Explain and compare BFS,DFS,IDS with respect to completeness, time and space complexity and optimality. Uninformed strategies use only the information available in the problem definition Also known as blind searching Breadth-first search Uniform-cost search Depth-first search Depth-limited search Iterative deepening search Completeness Will a solution always be found if one exists? Time How long does it take to find the solution? Often represented as the number of nodes searched Space How much memory is needed to perform the search? Often represented as the maximum number of nodes stored at once Optimal Will the optimal (least cost) solution be found?.. What is task environment? Explain different properties/types of task environment with examples Task environments are the problems and rational agents are solution to it. What is Task Environment (TE)? Performance Measure, Environment, Actuators and Sensors together constitute the TE. Must first specify the setting for intelligent agent design. What is Knowledge based agent? Explain the Wumpus world and its PEAS

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7 The Wumpus World is a cave consisting of rooms connected by passageways.. Lurking somewhere in the cave is the terrible Wumpus, a beast that eats anyone who enters in the room Performance measure - gold +00, falling in the pit and being eating per step, - for using the arrow The game ends when the agent dies or climbs Environment A 4X4 grid of rooms. The agent always starts in the square labeled [1,1], facing to the right. The locations of the gold and the wumpus are Actuators: -Left turn, Right turn, Forward, Grab, Release, Shoot Grab can be used to pick up the gold Shoot is used to fire an arrow Climb is used to climb out of the cave. Sensors: -Stench, Breeze, Glitter, Bump, Scream What is Entailment? Model the presence of pits in squares [1,2] [2,2] and [3,1]. Let α1 models no pits in [1,2]. Then, does KB = α1? Entailment means that one thing follows from another: p = q means p entails the sentence q. In every model, in which p is true, q is also true. The truth of q is contained in p eg, a + b=9 = 9=a + b Sentence x = 0 entails the sentence xy = 0.

8 In every model for which KB is true, α1 must be true( as no breeze in [1,1]), there cant be a pit in the adjacent square [1,2]. KB = α1 *************