csci 5582 fall 2006 csci 5582 artificial intelligence lecture 8 jim martin
Post on 20-Dec-2015
214 views
TRANSCRIPT
![Page 1: CSCI 5582 Fall 2006 CSCI 5582 Artificial Intelligence Lecture 8 Jim Martin](https://reader033.vdocument.in/reader033/viewer/2022051619/56649d535503460f94a30019/html5/thumbnails/1.jpg)
CSCI 5582 Fall 2006
CSCI 5582Artificial
IntelligenceLecture 8Jim Martin
![Page 2: CSCI 5582 Fall 2006 CSCI 5582 Artificial Intelligence Lecture 8 Jim Martin](https://reader033.vdocument.in/reader033/viewer/2022051619/56649d535503460f94a30019/html5/thumbnails/2.jpg)
CSCI 5582 Fall 2006
Today 9/26
• Review• Knowledge-Based Agents• Break• Propositional logic
![Page 3: CSCI 5582 Fall 2006 CSCI 5582 Artificial Intelligence Lecture 8 Jim Martin](https://reader033.vdocument.in/reader033/viewer/2022051619/56649d535503460f94a30019/html5/thumbnails/3.jpg)
CSCI 5582 Fall 2006
Review
• We studied search because it facilitates the creation of agents that can reason about hypothetical (future) states of the world.
• But… we haven’t said much of anything about how those states should be represented.
• Or about how these future (successor) states can be generated from current states
![Page 4: CSCI 5582 Fall 2006 CSCI 5582 Artificial Intelligence Lecture 8 Jim Martin](https://reader033.vdocument.in/reader033/viewer/2022051619/56649d535503460f94a30019/html5/thumbnails/4.jpg)
CSCI 5582 Fall 2006
Knowledge-Based Agents
• A knowledge-base is simply a repository of things you know represented in some useful way.
• A knowledge-based agent is one that chooses its actions at least in part on the basis of the contents of its knowledge-base.
![Page 5: CSCI 5582 Fall 2006 CSCI 5582 Artificial Intelligence Lecture 8 Jim Martin](https://reader033.vdocument.in/reader033/viewer/2022051619/56649d535503460f94a30019/html5/thumbnails/5.jpg)
CSCI 5582 Fall 2006
Knowledge Representation
• A knowledge representation is a formal scheme that dictates how an agent is going to represent its knowledge.– Syntax: Rules that determine the possible strings in the language.
– Semantics: Rules that determine a mapping from sentences in the representation to some particular state of affairs.
![Page 6: CSCI 5582 Fall 2006 CSCI 5582 Artificial Intelligence Lecture 8 Jim Martin](https://reader033.vdocument.in/reader033/viewer/2022051619/56649d535503460f94a30019/html5/thumbnails/6.jpg)
CSCI 5582 Fall 2006
Reasoning
• The knowledge base can’t be a simple table.– It has to be set up so that an agent can conclude facts about the world that are not already represented in the knowledge base.
– In other words, it has to reason about unseen worlds
![Page 7: CSCI 5582 Fall 2006 CSCI 5582 Artificial Intelligence Lecture 8 Jim Martin](https://reader033.vdocument.in/reader033/viewer/2022051619/56649d535503460f94a30019/html5/thumbnails/7.jpg)
CSCI 5582 Fall 2006
Reasoning
![Page 8: CSCI 5582 Fall 2006 CSCI 5582 Artificial Intelligence Lecture 8 Jim Martin](https://reader033.vdocument.in/reader033/viewer/2022051619/56649d535503460f94a30019/html5/thumbnails/8.jpg)
CSCI 5582 Fall 2006
Wumpus World Description
• Percepts: Breeze, Glitter, Smell• Actions: Left, Right, Forward, Back, Shoot, Grab, Release
• Goals: Get the gold, get back to the start, (avoiding the Wumpus, and the pits).
![Page 9: CSCI 5582 Fall 2006 CSCI 5582 Artificial Intelligence Lecture 8 Jim Martin](https://reader033.vdocument.in/reader033/viewer/2022051619/56649d535503460f94a30019/html5/thumbnails/9.jpg)
CSCI 5582 Fall 2006
Wumpus World
![Page 10: CSCI 5582 Fall 2006 CSCI 5582 Artificial Intelligence Lecture 8 Jim Martin](https://reader033.vdocument.in/reader033/viewer/2022051619/56649d535503460f94a30019/html5/thumbnails/10.jpg)
CSCI 5582 Fall 2006
Wumpus World
• Environment– One Wumpus– One or more pits– Squares adjacent to pits have a breeze
– Squares adjacent to the Wumpus have a stench
– Glitter is detected only in squares with the gold
![Page 11: CSCI 5582 Fall 2006 CSCI 5582 Artificial Intelligence Lecture 8 Jim Martin](https://reader033.vdocument.in/reader033/viewer/2022051619/56649d535503460f94a30019/html5/thumbnails/11.jpg)
CSCI 5582 Fall 2006
Start: Percept[None]
A
![Page 12: CSCI 5582 Fall 2006 CSCI 5582 Artificial Intelligence Lecture 8 Jim Martin](https://reader033.vdocument.in/reader033/viewer/2022051619/56649d535503460f94a30019/html5/thumbnails/12.jpg)
CSCI 5582 Fall 2006
Start: Percept [None]
![Page 13: CSCI 5582 Fall 2006 CSCI 5582 Artificial Intelligence Lecture 8 Jim Martin](https://reader033.vdocument.in/reader033/viewer/2022051619/56649d535503460f94a30019/html5/thumbnails/13.jpg)
CSCI 5582 Fall 2006
Percept [Breeze]
![Page 14: CSCI 5582 Fall 2006 CSCI 5582 Artificial Intelligence Lecture 8 Jim Martin](https://reader033.vdocument.in/reader033/viewer/2022051619/56649d535503460f94a30019/html5/thumbnails/14.jpg)
CSCI 5582 Fall 2006
Percept [Breeze]
![Page 15: CSCI 5582 Fall 2006 CSCI 5582 Artificial Intelligence Lecture 8 Jim Martin](https://reader033.vdocument.in/reader033/viewer/2022051619/56649d535503460f94a30019/html5/thumbnails/15.jpg)
CSCI 5582 Fall 2006
Percept [Stench]
![Page 16: CSCI 5582 Fall 2006 CSCI 5582 Artificial Intelligence Lecture 8 Jim Martin](https://reader033.vdocument.in/reader033/viewer/2022051619/56649d535503460f94a30019/html5/thumbnails/16.jpg)
CSCI 5582 Fall 2006
Percept []
![Page 17: CSCI 5582 Fall 2006 CSCI 5582 Artificial Intelligence Lecture 8 Jim Martin](https://reader033.vdocument.in/reader033/viewer/2022051619/56649d535503460f94a30019/html5/thumbnails/17.jpg)
CSCI 5582 Fall 2006
Logic
• Lots of different logics• Some differ primarily in their syntax
• More importantly they differ in how they view the world
![Page 18: CSCI 5582 Fall 2006 CSCI 5582 Artificial Intelligence Lecture 8 Jim Martin](https://reader033.vdocument.in/reader033/viewer/2022051619/56649d535503460f94a30019/html5/thumbnails/18.jpg)
CSCI 5582 Fall 2006
Logics
• Propositional logic• First order logic (predicate calculus)
• Probability theory
![Page 19: CSCI 5582 Fall 2006 CSCI 5582 Artificial Intelligence Lecture 8 Jim Martin](https://reader033.vdocument.in/reader033/viewer/2022051619/56649d535503460f94a30019/html5/thumbnails/19.jpg)
CSCI 5582 Fall 2006
Admin/Break
• The quiz…– There were three clear categories of folks•Those who relied on their recollection of the lectures
•Those who read the book (carefully)•Those who did both
– I’ll give back the quiz and the first HW on Thursday
![Page 20: CSCI 5582 Fall 2006 CSCI 5582 Artificial Intelligence Lecture 8 Jim Martin](https://reader033.vdocument.in/reader033/viewer/2022051619/56649d535503460f94a30019/html5/thumbnails/20.jpg)
CSCI 5582 Fall 2006
Quiz 2
• Scheduled for Oct 19. • Covers chapters …7,8,9, 13 and 14.
![Page 21: CSCI 5582 Fall 2006 CSCI 5582 Artificial Intelligence Lecture 8 Jim Martin](https://reader033.vdocument.in/reader033/viewer/2022051619/56649d535503460f94a30019/html5/thumbnails/21.jpg)
CSCI 5582 Fall 2006
Propositional Logic
• Atomic Propositions• That are true or false• Connectives to form sentences that receive truth conditions based on a compositional semantics
![Page 22: CSCI 5582 Fall 2006 CSCI 5582 Artificial Intelligence Lecture 8 Jim Martin](https://reader033.vdocument.in/reader033/viewer/2022051619/56649d535503460f94a30019/html5/thumbnails/22.jpg)
CSCI 5582 Fall 2006
Inference
• Simple Compositional semantics• Modus ponens• Resolution• Model-Checking
![Page 23: CSCI 5582 Fall 2006 CSCI 5582 Artificial Intelligence Lecture 8 Jim Martin](https://reader033.vdocument.in/reader033/viewer/2022051619/56649d535503460f94a30019/html5/thumbnails/23.jpg)
CSCI 5582 Fall 2006
Compositional Semantics
• The semantics of a complex sentence is derived from the semantics of its parts BA∨
![Page 24: CSCI 5582 Fall 2006 CSCI 5582 Artificial Intelligence Lecture 8 Jim Martin](https://reader033.vdocument.in/reader033/viewer/2022051619/56649d535503460f94a30019/html5/thumbnails/24.jpg)
CSCI 5582 Fall 2006
Compositional Semantics
• Syntactic Manipulations– And elimination– And introduction– Or introduction– Double negation removal
![Page 25: CSCI 5582 Fall 2006 CSCI 5582 Artificial Intelligence Lecture 8 Jim Martin](https://reader033.vdocument.in/reader033/viewer/2022051619/56649d535503460f94a30019/html5/thumbnails/25.jpg)
CSCI 5582 Fall 2006
Compositional Semantics
• And introduction• You know
• You can add
B
A
BA∧
![Page 26: CSCI 5582 Fall 2006 CSCI 5582 Artificial Intelligence Lecture 8 Jim Martin](https://reader033.vdocument.in/reader033/viewer/2022051619/56649d535503460f94a30019/html5/thumbnails/26.jpg)
CSCI 5582 Fall 2006
Modus Ponens
• You know
• What can you conclude?
BA
A
→
B
![Page 27: CSCI 5582 Fall 2006 CSCI 5582 Artificial Intelligence Lecture 8 Jim Martin](https://reader033.vdocument.in/reader033/viewer/2022051619/56649d535503460f94a30019/html5/thumbnails/27.jpg)
CSCI 5582 Fall 2006
Inference
• Why?– Because if A implies B and you know A then you know B •(Wrong)
– Because the truth table for the -> connective has B being true for all the entries where A->B is true and A is true (right).
![Page 28: CSCI 5582 Fall 2006 CSCI 5582 Artificial Intelligence Lecture 8 Jim Martin](https://reader033.vdocument.in/reader033/viewer/2022051619/56649d535503460f94a30019/html5/thumbnails/28.jpg)
CSCI 5582 Fall 2006
Resolution
• You know
• What can you conclude?
CB
BA
∨¬∨
CA∨
![Page 29: CSCI 5582 Fall 2006 CSCI 5582 Artificial Intelligence Lecture 8 Jim Martin](https://reader033.vdocument.in/reader033/viewer/2022051619/56649d535503460f94a30019/html5/thumbnails/29.jpg)
CSCI 5582 Fall 2006
Inference
• Inference must be a purely formal, syntactic, mechanical, dumb, physical (preferably fast) process
![Page 30: CSCI 5582 Fall 2006 CSCI 5582 Artificial Intelligence Lecture 8 Jim Martin](https://reader033.vdocument.in/reader033/viewer/2022051619/56649d535503460f94a30019/html5/thumbnails/30.jpg)
CSCI 5582 Fall 2006
Modeling Wumpus World
• Environmental state• No stench in 1,1
1,1S¬
![Page 31: CSCI 5582 Fall 2006 CSCI 5582 Artificial Intelligence Lecture 8 Jim Martin](https://reader033.vdocument.in/reader033/viewer/2022051619/56649d535503460f94a30019/html5/thumbnails/31.jpg)
CSCI 5582 Fall 2006
Modeling Wumpus World
• Long term rules of the world– Breezes are found in states adjacent to pits
– Stenches are found in states adjacent to Wumpi
– No stench means no Wumpus nearby
• For example…¬S1,1 → ¬W1,1 ^ ¬W2,1 ^ ¬W1,2
![Page 32: CSCI 5582 Fall 2006 CSCI 5582 Artificial Intelligence Lecture 8 Jim Martin](https://reader033.vdocument.in/reader033/viewer/2022051619/56649d535503460f94a30019/html5/thumbnails/32.jpg)
CSCI 5582 Fall 2006
Alternative Schemes
• Wumpi cause stenches
Or
S1,1 implies W1,1 or W1,2 or W2,1
1,22,11,11,1 SSSW ∧∧→
1,22,11,11,1 WWWS ∨∨→
Causal rule
Diagnostic rule
![Page 33: CSCI 5582 Fall 2006 CSCI 5582 Artificial Intelligence Lecture 8 Jim Martin](https://reader033.vdocument.in/reader033/viewer/2022051619/56649d535503460f94a30019/html5/thumbnails/33.jpg)
CSCI 5582 Fall 2006
Inference in Wumpus World
![Page 34: CSCI 5582 Fall 2006 CSCI 5582 Artificial Intelligence Lecture 8 Jim Martin](https://reader033.vdocument.in/reader033/viewer/2022051619/56649d535503460f94a30019/html5/thumbnails/34.jpg)
CSCI 5582 Fall 2006
Limitations
• Can we represent…– The breeze or stench rules with all their implications?
– A pit, two pits, some pits, no pits?– A wumpus…
![Page 35: CSCI 5582 Fall 2006 CSCI 5582 Artificial Intelligence Lecture 8 Jim Martin](https://reader033.vdocument.in/reader033/viewer/2022051619/56649d535503460f94a30019/html5/thumbnails/35.jpg)
CSCI 5582 Fall 2006
Next time
• Finish Chapter 7, start on 8