{[ promptMessage ]}

Bookmark it

{[ promptMessage ]}

Lecture-09-10-Logical Agents

Lecture-09-10-Logical Agents - CS 561 Artificial...

Info icon This preview shows pages 1–8. Sign up to view the full content.

View Full Document Right Arrow Icon
CS 561: Artificial Intelligence Instructor: Sofus A. Macskassy, [email protected] TAs: Nadeesha Ranashinghe ( [email protected] ) William Yeoh ( [email protected] ) Harris Chiu ( [email protected] ) Lectures: MW 5:00-6:20pm, OHE 122 / DEN Office hours: By appointment Class page: http://www-rcf.usc.edu/~macskass/CS561-Spring2010/ This class will use http://www.uscden.net/ and class webpage - Up to date information - Lecture notes - Relevant dates, links, etc. Course material: [AIMA] Artificial Intelligence: A Modern Approach, by Stuart Russell and Peter Norvig. (2nd ed)
Image of page 1

Info icon This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
CS561 - Lecture 09-10 - Macskassy - Spring 2010 2 Logical Agents [AIMA Ch. 7] Knowledge-based agents Wumpus world Logic in general models and entailment Propositional (Boolean) logic Equivalence, validity, satisfiability Inference rules and theorem proving forward chaining backward chaining resolution
Image of page 2
CS561 - Lecture 09-10 - Macskassy - Spring 2010 3 Knowledge bases Knowledge base = set of sentences in a formal language Declarative approach to building an agent (or other system): T ELL it what it needs to know Then it can A SK itself what to do answers should follow from the KB Agents can be viewed at the knowledge level i.e., what they know , regardless of how implemented Or at the implementation level i.e., data structures in KB and algorithms that manipulate them
Image of page 3

Info icon This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
Knowledge-Based Agent Agent that uses prior or acquired knowledge to achieve its goals Can make more efficient decisions Can make informed decisions Knowledge Base (KB): contains a set of representations of facts about the Agent’s environment Each representation is called a sentence Use some knowledge representation language , to T ELL it what to know e.g., (temperature 72F) A SK agent to query what to do Agent can use inference to deduce new facts from T ELL ed facts Knowledge Base Inference engine Domain independent algorithms Domain specific content TELL ASK 4 CS561 - Lecture 09-10 - Macskassy - Spring 2010
Image of page 4
CS561 - Lecture 09-10 - Macskassy - Spring 2010 5 A simple knowledge-based agent The agent must be able to: Represent states, actions, etc. Incorporate new percepts Update internal representations of the world Deduce hidden properties of the world Deduce appropriate actions
Image of page 5

Info icon This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
CS561 - Lecture 09-10 - Macskassy - Spring 2010 6 Wumpus World Example Performance measure gold +1000, death -1000 -1 per step, -10 for using the arrow Environment Squares adjacent to wumpus are smelly Squares adjacent to pit are breezy Glitter iff gold is in the same square Shooting kills wumpus if you are facing it Shooting uses up the only arrow Grabbing picks up gold if in same square Releasing drops the gold in same square Actuators Left turn, Right turn, Forward, Grab, Release, Shoot Sensors Breeze, Glitter, Smell
Image of page 6
Wumpus world characterization Observable?
Image of page 7

Info icon This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
Image of page 8
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}

What students are saying

  • Left Quote Icon

    As a current student on this bumpy collegiate pathway, I stumbled upon Course Hero, where I can find study resources for nearly all my courses, get online help from tutors 24/7, and even share my old projects, papers, and lecture notes with other students.

    Student Picture

    Kiran Temple University Fox School of Business ‘17, Course Hero Intern

  • Left Quote Icon

    I cannot even describe how much Course Hero helped me this summer. It’s truly become something I can always rely on and help me. In the end, I was not only able to survive summer classes, but I was able to thrive thanks to Course Hero.

    Student Picture

    Dana University of Pennsylvania ‘17, Course Hero Intern

  • Left Quote Icon

    The ability to access any university’s resources through Course Hero proved invaluable in my case. I was behind on Tulane coursework and actually used UCLA’s materials to help me move forward and get everything together on time.

    Student Picture

    Jill Tulane University ‘16, Course Hero Intern