AI: Introduction to artificial intelligencePresentation Transcript
Introduction to Artificial Intelligence
Some Definitions of AI “It is the exciting new effort to make computers think . . . machines with minds, in the full and literal sense”(Haugeland, 1985) “A field of study that seeks to explain and emulate intelligent behavior in terms of computational processes”(Schalkoff, 1990) “The study of how to make computers do things at which, at the moment, people are better”(Rich and Knight, 1991 ) “The study of the computations that make it possible to perceive, reason, and act”(Winston, 1992)
Categories of AI systems Systems that think like humans. Systems that think rationally. Systems that act like humans. Systems that act rationally. Acting humanly: The Turing Test approach
Requirements of an Artificially intelligent computer Natural language processing to enable it to communicate successfully in English (or some other human language); Knowledge representation to store information provided before or during the interrogation; Automated reasoning to use the stored information to answer questions and to draw new conclusions; Machine learning to adapt to new circumstances and to detect and extrapolate patterns.
History of AI 1943 : The gestation of AI 1952 : Early enthusiasm and expectation 1966 : A dose of reality 1969 : Knowledge based system 1980 : AI become Industry 1986 …to now : Return of neural networks and recent events
AI in real world HITECH is the first computer program to defeat a grandmaster(Arnold Denker) in a game of chess A speech understanding program named PEGASUS handles the whole transaction of ticket booking in an Airport
What is an Intelligent Agents? An agent is anything that can be viewed as perceiving its environment through sensors and acting upon that environment through effectors. An agent always acts rationally.
Example of Car driver agent : Agent type : Car driving Percepts : Camera , GPS, mic etc Action : Steer, Accelerate, Break, Report. Goal : Safe, Fast, Profit. Environment : Roads, Signals, Pedestrians.
Different types of agent programs Simple reflex agents Agents that keep track of the world Goal-based agents Utility-based agents
What are Simple reflex Agents? Agents are designed to produce a specific response to a specific stimuli.
What are Agents that keep track of the world? The simple reflex agent described before will work only if the correct decision can be made on the basis of the current percept. If the car in front is a recent model, and has the centrally mounted brake system, then it is to be possible to tell if it is braking from a single image agent will have to maintain some sort of internal state in order to choose an action. This is overcome in this kind of Agents.
What are Goal-based agents? These Kind of agents take decision based on how far they are currently from their goal. Their every action is intended to reduce its distance from goal.
What are Utility-based agents? The agents which are developed having their end uses as their building blocks are called utility based agents.
Classifications of Agent environment can be based on : Accessible vs. Inaccessible. Deterministic vs. Nondeterministic. Episodic vs. Non episodic. Static vs. Dynamic Discrete vs. Continuous
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