Fundamentals of AI Introduction COSC 159 Fundamentals of

Fundamentals of AI Introduction COSC 159 - Fundamentals of AI

Overview Syllabus Grading l Topics l What is AI? l Four competing views Agents Course Goals Summary COSC 159 - Fundamentals of AI 2

Syllabus Instructor information Prerequisites l Programming Languages Textbook l Russell and Norvig, AIMA, 2 nd Edition Attendance COSC 159 - Fundamentals of AI 3

Grading Qualities of good work Communication l Correctness l Validation l Comparison l Efficiency l Your work will be graded on all aspects COSC 159 - Fundamentals of AI 4

Topics Covered Definitions of AI Agents Problem representation and solving l Searching, heuristics, optimization Knowledge representation and reasoning l Logic Planning problems Uncertainty Learning More topics if we have time COSC 159 - Fundamentals of AI 5

What is AI? Understand build intelligent entities l Artificial refers to building entities What is intelligence? Understand build an entity emulating a human? l Understand build an entity that is rational? l COSC 159 - Fundamentals of AI 6

Rationality An ideal concept of intelligence Doing the right thing given available information l How do we define the right thing? l Suppose put your hand down on a hot stove. What is the rational response? Rationality does not always mean doing the best possible thing COSC 159 - Fundamentals of AI 7

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Rationality Given the situation, was the boss’ action irrational? What would make the boss’ action irrational? COSC 159 - Fundamentals of AI 9

Competing Views of AI Many definitions that can be classified as follows (Russell and Norvig, 2003) Like Humans Rationally Thinking Acting COSC 159 - Fundamentals of AI 10

Acting Humanly Turing test (1950) COSC 159 - Fundamentals of AI 11

Acting Humanly Goal: Make computers/entities act like humans l l Natural language processing Knowledge representation Automated reasoning Machine learning It is not important how the actions are chosen, as long as results in behavior indistinguishable from a human COSC 159 - Fundamentals of AI 12

Thinking Humanly Understand cognition l Defined as the mental process of knowing, including aspects such as awareness, perception, reasoning, and judgment. Simulate cognition on computers Cognitive science l Experimental investigation of humans and animals The how is important COSC 159 - Fundamentals of AI 13

Thinking Rationally Attempt to codify “right thinking” l Aristotle’s syllogisms (reasonings or patterns of argument) Logical approach l l Formal methods of representing knowledge Formal methods of reasoning Again, how a conclusion is reached is important COSC 159 - Fundamentals of AI 14

Acting Rationally Entities that do the right thing The how isn’t necessarily important Couple rational thinking with other methods l What if there is no provably correct action? l Consider the hot stove again l Did the action require rational thought? Are reflex actions intelligent? COSC 159 - Fundamentals of AI 15

Applications Autonomous planning and scheduling l NASA’s Remote Agent Game playing l IBM’s Deep Blue Autonomous control l ALVINN, drove 98% of the time across the country Diagnosis l Medical diagnosis Pattern recognition l Data mining and bioinformatics COSC 159 - Fundamentals of AI 16

Characteristics of AI Problems Frequently hard l NP-hard, which implies there is no known efficient general solution Frequently complex l Messy data, such as images, pressure, locations, natural language, etc. Frequently imprecise l Uncertain situations Autonomy l Cannot require human intervention, must adapt COSC 159 - Fundamentals of AI 17

Agents An agent is something that acts In this class, we will build software agents l Agents that act rationally How are agents different from other programs? l l l Autonomous Perceptive Persistent Adaptable Assume the goals of other agents COSC 159 - Fundamentals of AI 18

Agents Agent Sensors Percepts Environment ? Actuators Actions COSC 159 - Fundamentals of AI 19

Definitions Percept sequence l History of everything agent has perceive Agent function l Map from percept sequence to action Agent program l Implementation of agent function COSC 159 - Fundamentals of AI 20

Example Consider a world that has a starving monkey and a banana. Whenever the monkey is in the same location as the banana, the monkey will eat it. After eating the banana, the monkey falls asleep. We would like to build a simulation for the environment with a software agent representing the monkey. Consider a world with two locations. COSC 159 - Fundamentals of AI 21

Example U D COSC 159 - Fundamentals of AI 22

Example Assumptions Monkey can see the bananas and knows its location l Defines percepts: (Location, Contents) l Actions l Up, down, eat, sleep COSC 159 - Fundamentals of AI 23

Example Agent function should move monkey to the bananas, eat the bananas, then sleep One possible agent program is to create a table mapping a percept sequence to appropriate action l Table-driven agent COSC 159 - Fundamentals of AI 24

Table Percept Sequence Action (U, Empty) Down (U, Bananas) Eat (D, Empty) Up … (U, Empty), (D, Bananas) Eat (U, Bananas), (U, Empty) Sleep … (D, Empty), (U, Bananas), (U, Empty) COSC 159 - Fundamentals of AI ? ? ? 25

Questions to ponder Is a table driven agent a good way to implement rational behavior? Are all sequences of percepts possible in the environment? What if the monkey didn’t know its location, could you still devise a solution to the problem? How would the percepts change? COSC 159 - Fundamentals of AI 26

Measuring Rational Behavior What does it mean for an agent to do the right thing? l The right action is the one causing the agent to be most successful. A performance measure embodies the criterion for an agent’s success. COSC 159 - Fundamentals of AI 27

Performance Measures Simple performance measure for monkey and bananas l The monkey has eaten and fallen asleep. Suppose you have two monkeys, one that sleeps right after eating and one that wanders around and then falls asleep. Which one is better? Why? COSC 159 - Fundamentals of AI 28

Performance Measures Consider more complex environments l l What performance measure is appropriate for the economy? What about for stocks? How about medical diagnoses? What about driving a car? Performance measures are not easy to determine, but you must design one for each environment COSC 159 - Fundamentals of AI 29

Rationality Rational behavior at any given time depends on four things Performance measure l Agent’s prior knowledge l Actions agent can perform l Agent’s percept sequence l COSC 159 - Fundamentals of AI 30

Course Goals Understand build intelligent entities l Rational agents Formulate search problems l Solve using uninformed and informed algorithms Represent and reason about knowledge l Logic Formulate and solve planning problems l STRIPS, partial order planners COSC 159 - Fundamentals of AI 31

Course Goals (cont. ) Reason in uncertain situations l Probability, Bayesian networks Introduce machine learning l Inductive learning, decision trees COSC 159 - Fundamentals of AI 32

For Next Time Read through chapters 1 and 2. Think about how you would implement a simulation for the two location monkey and banana world. COSC 159 - Fundamentals of AI 33

Summary AI is the study and implementation of intelligent entities Several perspectives on AI l We will take the rational action perspective The agent framework provides a unifying approach to AI Applications of AI are widespread and complex COSC 159 - Fundamentals of AI 34