Knowledge Representation - Embedded Intelligent Robotics - Lecture Slides, Slides of Robotics

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Knowledge Representation

Representation

• Set of syntactic and semantic conventions

which make it possible to describe things

• Syntax
  • specific symbols allowed and rules allowed
• Semantics
  • how meaning is associated with symbol arrangements allowed by syntax

Types of Knowledge

• Objects
  • both physical & concepts
• Events
  • usually involve time
  • maybe cause & effect relationships
• Performance
  • how to do things
• META Knowledge
  • knowledge about how to use knowledge

Stages of Knowledge Use

• Acquisition
  • structure of facts
  • integration of old & new knowledge
• Retrieval (recall)
  • roles of linking and chunking
  • means of improving recall efficiency

Knowledge Representation Issues

• Grain size or resolution detail
• Scope or domain
• Modularity
• Understandability
• Explicit versus implicit knowledge
• Procedural versus declarative knowledge

Advantages

• Declarative representation
  • Store each fact once
  • Easy to add new facts
• Procedural representation
  • Easy to represent "how to do things"
  • Easy to represent any knowledge not fitting declarative format
  • Relatively easy to implement heuristic stuff on doing thing efficiently

Attributes of Good KR Schemes

• Acquisitional Efficiency
  • easy to add new knowledge
• Semantic Power
  • Supports truth theory
  • Provides for constraint satisfaction
  • Can cope with incomplete or uncertain knowledge
  • Contains some commonsense reasoning capability

Broad KR Questions

• Are there properties of objects so basic that they occur in every domain?
• If so what are they?
• At what level should knowledge be represented?
• Is there a good set of primitives into which all knowledge can be broken down?
• How can the relevant parts of a large knowledge base be accessed when needed?

Two Approaches

• Use complete object descriptions that include

relations to other objects in the environment

• Use predicate logic to express these kind of

relations

on(plant,table). under(table,window). in(table,room).

Frame Problem

• What (or how much) should be stored at each node?
• How do you distinguish between facts that change from facts that do not change between frames?
• Stated and another way, how do you decide how much information to record as you move from problem state to problem state?

Frame Problem

• Better solution is to not physically modify the state description but merely record a list of changes that should be made at this node
• To get to the current state, you start at the initial state and then apply the changes recorded
• Backtracking will be easy, but state description is complicated

Frame Problem

• Another alternative would be to modify the

state description but mark the changes made

so they can be undone when backtracking is

required

• If temporal relations (time) are involved things

will become regardless of the approach used