Intelligent System
CS306- INTELLIGENT SYSTEMS
Part – A 1. There are well-known classes of problems that are intractably difficult for computers, and other classes that are provably undecidable. Does this mean AI is impossible? (2)
No, it means that AI systems should avoid trying to solve intractable problems. Usually this means they can only approximate optimal behavior. Notice that even humans do not solve NP- complete problems. Sometimes they are good at solving specific instances with a lot of structure , perhaps with the aid of background knowledge. AI systems should attempt to do the same 2. “A rational agent need not be omniscient, but it has to be autonomous”. Do you agree with the statement? Justify your answer. (2) In real world scenario, knowing the actual outcome of the action and acting accordingly is impossible. Rationality depends on the percept sequence to date and hence omniscience is not compulsory. As a rational agent should learn what it can, so that it can compensate partial/incorrect prior knowledge, it must depend on its own percepts rather than prior knowledge supplied by the designer. Hence it should be autonomous.
3. For each of the following activities, give a PEAS description of the task environment a) Playing soccer.
Performance measure: To play, make goals and win the game.
Environment: Soccer field, teammates and opponents, referee, audience.
Actuator: Navigator, legs of robot, view detector for robot.
Sensors: Camera, communicators, sensors. (0.5)
b) Exploring the subsurface oceans of Titan Performance measure: Surface area mapped, extraterrestrial life found
Environment: subsurface oceans of Titan Actuator: steering, accelerator, break, probe arm,
Sensors: camera, sonar, probe sensors. (0.5)
c) Shopping for used AI books on the Internet
Performance measure: Cost of book, quality/relevance/correct edition
Environment: Internet’s used book shops.
Actuator: key entry, cursor
Part – A 1. There are well-known classes of problems that are intractably difficult for computers, and other classes that are provably undecidable. Does this mean AI is impossible? (2)
No, it means that AI systems should avoid trying to solve intractable problems. Usually this means they can only approximate optimal behavior. Notice that even humans do not solve NP- complete problems. Sometimes they are good at solving specific instances with a lot of structure , perhaps with the aid of background knowledge. AI systems should attempt to do the same 2. “A rational agent need not be omniscient, but it has to be autonomous”. Do you agree with the statement? Justify your answer. (2) In real world scenario, knowing the actual outcome of the action and acting accordingly is impossible. Rationality depends on the percept sequence to date and hence omniscience is not compulsory. As a rational agent should learn what it can, so that it can compensate partial/incorrect prior knowledge, it must depend on its own percepts rather than prior knowledge supplied by the designer. Hence it should be autonomous.
3. For each of the following activities, give a PEAS description of the task environment a) Playing soccer.
Performance measure: To play, make goals and win the game.
Environment: Soccer field, teammates and opponents, referee, audience.
Actuator: Navigator, legs of robot, view detector for robot.
Sensors: Camera, communicators, sensors. (0.5)
b) Exploring the subsurface oceans of Titan Performance measure: Surface area mapped, extraterrestrial life found
Environment: subsurface oceans of Titan Actuator: steering, accelerator, break, probe arm,
Sensors: camera, sonar, probe sensors. (0.5)
c) Shopping for used AI books on the Internet
Performance measure: Cost of book, quality/relevance/correct edition
Environment: Internet’s used book shops.
Actuator: key entry, cursor