Knowledge Representation Weve discussed generic search techniques Usually
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Knowledge Representation • We’ve discussed generic search techniques. • Usually we start out with a generic technique and enhance it to take advantage of a specific domain. • The representation of knowledge about the domain is a major issue. • Picking a good representation can make a big difference. 1
Knowledge & Mappings • Knowledge is a collection of “facts” from some domain. • What we need is a representation of facts that can be manipulated by a program. – Some symbolic representation is necessary. – Need to be able to map facts to symbols. – Need to be able to map symbols to facts? 2
A. I. Problems & K. R. • Game playing - need rules of the game, strategy, heuristic function(s). • Expert Systems - list of rules, methods to extract new rules. • Learning - the space of all things learnable (domain representation), concept representation. • Natural Language - symbols, groupings, semantic mappings, . . . 3
Representation Properties Representational Adequacy - Is it possible to represent everything of interest ? Inferential Adequacy - Can new information be inferred? Inferential Efficiency - How easy is it to infer new knowledge? Acquisitional Efficiency - How hard is it to gather information (knowledge)? 4
Using Logic ro Represent Facts • Logic representation is common in AI programs: Spot is a dog(Spot) All dogs have tails x: dogs(x)->hastail(x) Spot has a tail hastail(Spot) 5
Relational Databases • One way to store declarative facts is with a relational database: • Collection of attributes and values. 6
Inheritance • It is often useful to provide a representation structure that directly supports inference mechanisms. • Property Inheritance is a common inference mechanism. • Objects belong to classes. • Classes have properties that are inherited by objects that belong to the class. 7
Class Hierarchy • Classes are arranged in a hierarchy, so that some classes are members of more general classes. • There a variety of representation strategies used in AI that are based on inheritance: slot-and-filler semantic network frame system 8
Animal NO YES fly? YES Mammal Bat fly? Dog Under. Dog fly? Bird Penguin Sam YES fly? NO color BLACK color RED 9
Inheritance Algorithm • We want to find the value of the attribute a of a specific object o. • First look at object o itself. • Next look for an instance attribute and look there for the value of a. • If still no attribute a, check out all isa attributes. 10
Important Attributes • The instance and isa attributes support property inheritance. • Instance and isa may go by other names, or may be implicitly represented. • The isa (class membership) attribute is transitive. 11
Attributes as objects • Attributes are themselves objects that have properties: – Inverse – Existence in a hierarchy – Techniques for reasoning about values – Single-valued attributes 12
Inferential Knowledge • Inheritance is not the only inferential mechanism - logic formulas are often used: • We will study logical based inference procedures soon. 13
Procedural Knowledge • Some knowledge in contained in the code we write (for example, a hard coded chess strategy). • How does procedural knowledge do with respect to the representation properties: – Representational Adequacy – Inferential Efficiency – Acquisitional Efficiency 14
Granularity of Representation • High-level facts may require lots of storage if represented as a collection of low-level primitives. • Most knowledge is available in a high-level form (English). • It is not always clear what low-level primitives should be. 15
Representing Sets of Object • Extensional definition: list all members of a set. – Dorks = {Bill, Bob, Dave, Jane} • Intensional: use rules to define membership in a set: – Dork = {x: geek(x) and bald(x) } 16
Search and State Representation • Each state could be represented as a collection of facts. • Keeping many such states in memory may be impossible. • Most facts will not change when we move from one state to another. 17
The Frame Problem • Determining how to best represent facts that change from state to state along with those facts that do not change is the Frame Problem. • Sometimes the hard part is determining which facts change and which do not. 18
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