AI Spring 2010 Lecture 8-9

AI Spring 2010 Lecture 8-9 - Artificial Intelligence...

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Click to edit Master subtitle style Artificial Intelligence Spring 2010 Instructor: Paul S. Rosenbloom
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22 Project 1 £ Available on Blackboard £ Due by end of day (11:59pm PST) on 2/23 l Penalty for late submission (after late days used) £ Solving Sudoko l Using greedy best-first search and steepest-ascent hill climbing l Two different heuristic functions l Some short questions for you to answer as well £ TA (Hyokyeong Lee) should be first line for questions about programming and can answer content-oriented questions as well l I can answer content-oriented questions as well
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33 This Week’s Lectures £ Knowledge-based agents £ Wumpus world £ Logic in general - models and entailment £ £ Equivalence, validity, satisfiability £ Inference rules and theorem proving Quite a bit of new terminology this week
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44 Knowledge-Based Agents £ So far we have seen agents use several problem-solving-oriented kinds of knowledge l Problem spaces (states and actions, models of E) l Including sensory information about states l Problems (initial and goal states) l Search algorithms (K about how to search) l Evaluation, utility, and objective functions l Control rules and islands (brief discussion) £ The focus has been on knowledge encoded (or formulated) for a particular manner of use l More procedurally encoded
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55 Knowledge-Based Agents (2) £ Starting now we focus on knowledge more broadly l How is it represented for a broad set of possible uses? l Not just to for a single class of problems l But for a range problems, communicating, reading, teaching, etc. ± Without the inherent ambiguity in natural language ± “John saw a diamond through the window and coveted it.” ± “John threw a brick through the window and broke it.” l Support agent generality r Syntax specifies the form of the knowledge l Semantics determines the meaning of the knowledge l How do we reason with it to answer general questions? l Combine multiple facts to derive new ones that are implicit ± l Inference processes syntax so as to reflect/respect semantics
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66 Knowledge-Based Agents (3) £ Inside the box (replacing the “?”) is: l A knowledge base (KB) of content l Both general and domain specific information l In its simplest form can think of it as enhanced state content l An inference engine (or knowledge architecture) l A domain-independent means of deriving conclusions from KB £ Need to understand both how to build inference engines and how to represent knowledge
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77 Knowledge Bases £ Knowledge base = set of sentences in a formal language £ I.e., in a knowledge representation language with a well defined syntax and semantics l £ Declarative approach to building agents (or other systems) l Tell KB what it needs to know l Ask KB for answers to questions Knowledge Base Tell Ask
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88 A Simple Knowledge-Based Agent £ The agent must be able to: l Represent states, actions, etc. l
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This note was uploaded on 03/05/2010 for the course CS 561 taught by Professor Moradi during the Spring '09 term at USC.

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AI Spring 2010 Lecture 8-9 - Artificial Intelligence...

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