UMBC CMSC 671 - NOTES (34 pages)

Previewing pages 1, 2, 16, 17, 18, 33, 34 of 34 page document View the full content.
View Full Document

NOTES



Previewing pages 1, 2, 16, 17, 18, 33, 34 of actual document.

View the full content.
View Full Document
View Full Document

NOTES

25 views


Pages:
34
School:
University of Maryland, Baltimore County
Course:
Cmsc 671 - Principles of Artificial Intelligence

Unformatted text preview:

CMSC 671 Fall 2005 Class 2 Tuesday September 6 Today s class What s an agent Definition of an agent Rationality and autonomy Types of agents Properties of environments Lisp a second look Intelligent Agents Chapter 2 How do you design an intelligent agent Definition An intelligent agent perceives its environment via sensors and acts rationally upon that environment with its effectors A discrete agent receives percepts one at a time and maps this percept sequence to a sequence of discrete actions Properties Autonomous Reactive to the environment Pro active goal directed Interacts with other agents via the environment What do you mean sensors percepts and effectors actions Humans Sensors Eyes vision ears hearing skin touch tongue gustation nose olfaction neuromuscular system proprioception Percepts At the lowest level electrical signals from these sensors After preprocessing objects in the visual field location textures colors auditory streams pitch loudness direction Effectors limbs digits eyes tongue Actions lift a finger turn left walk run carry an object The Point percepts and actions need to be carefully defined possibly at different levels of abstraction A more specific example Automated taxi driving system Percepts Video sonar speedometer odometer engine sensors keyboard input microphone GPS Actions Steer accelerate brake horn speak display Goals Maintain safety reach destination maximize profits fuel tire wear obey laws provide passenger comfort Environment U S urban streets freeways traffic pedestrians weather customers Different aspects of driving may require different types of agent programs Rationality An ideal rational agent should for each possible percept sequence do whatever actions will maximize its expected performance measure based on 1 the percept sequence and 2 its built in and acquired knowledge Rationality includes information gathering not rational ignorance If you don t know something find out Rationality Need a performance measure to say how



View Full Document

Access the best Study Guides, Lecture Notes and Practice Exams

Loading Unlocking...
Login

Join to view NOTES and access 3M+ class-specific study document.

or
We will never post anything without your permission.
Don't have an account?
Sign Up

Join to view NOTES and access 3M+ class-specific study document.

or

By creating an account you agree to our Privacy Policy and Terms Of Use

Already a member?