Introduction to AI: Chapter 4 - Knowledge Representation and Reasoning Quiz

Knowledge Representation and Reasoning (KRR)

• Knowledge-based agents are intelligent agents that have an explicit representation of knowledge that can be reasoned with.
• An intelligent agent needs knowledge about the real world for taking decisions and reasoning to act efficiently.

Logic in AI

• Logic is a vital tool to think about how computers store knowledge.
• Logic is a formal language in which knowledge can be expressed.
• In Artificial Intelligence, the representation of knowledge is done via logic.

Types of Logic

• Propositional Logic (PL): the simplest form of logic where all statements are made by propositions.
• Predicate Logic (First-order Logic): more expressive than propositional logic, can specify general statements concerning similar cases.

Propositional Logic

• A proposition is a declarative statement that is either true or false.
• Propositional logic may be viewed as a representation language that allows us to express and reason with statements that are either true or false.
• Syntax of propositional logic defines the allowable sentences for knowledge representation.
• Two types of propositions:
  • Atomic Propositions: simple propositions consisting of a single proposition symbol.
  • Compound Propositions: constructed by combining simpler or atomic propositions using logical operators.

Inference in Propositional Logic

• Inference is generating conclusions from evidence and facts.
• Inference rules are templates for generating valid arguments.
• Implication, Converse, Contrapositive, and Inverse are terminologies related to inference rules.

First-order/Predicate Logic

• A limitation of propositional logic is the impossibility to express general statements concerning similar cases.
• Predicate logic is concerned with the internal structure of sentences.
• It plays a crucial role in knowledge representation, which is a field within artificial intelligence and philosophy concerned with representing knowledge.

Knowledge-Based Agents

• Knowledge-based agents are those agents that have the capability of:
  • Maintaining an internal state of knowledge.
  • Reasoning over that knowledge.
  • Updating their knowledge after observations.
  • Taking actions.
• Knowledge-based agents are composed of two main parts:
  • Knowledge-base.
  • Inference system.
• The architecture of knowledge-based agents includes:
  • Perception of the environment.
  • Incorporation of new percepts.
  • Update of the internal representation of the world.
  • Reasoning of appropriate actions.