Lecture 3 Artificial Intelligence Fahad CSIT Lahore Leads

Lecture 3 Artificial Intelligence Fahad CS&IT, Lahore Leads University

Knowledge Representation

Overview Knowledge Processing § Motivation § Objectives § AI Life Cycle § Knowledge Types 3 3

Knowledge Representation l l A subarea of Artificial Intelligence concerned with understanding, designing, and implementing ways of representing information in computers so that programs (agents) can use this information • to derive information that is implied by it, to converse with people in natural

l l l to decide what to do next to plan future activities, to solve problems in areas that normally require human expertise

Catching My Plane o Scenario for an examination of knowledge representation and reasoning: o A traveller wants to know when he/she needs to leave his/her hotel in order to catch a plane o background knowledge situation knowledge acquisition of additional knowledge for decision making reasoning methods verification and validation o o

Computer Scenario l Traveler posts a query to a computer

Google:

Bing:

Ask. com:

Human Scenario l Traveler asks a human n e. g. hotel receptionist

Motivation § § Representation and manipulation of knowledge has been essential for the development of humanity as we know it Use of formal methods and support from machines can improve our knowledge representation and reasoning abilities Intelligent reasoning is a very complex phenomenon, and may have to be described in a variety of ways Basic understanding of knowledge representation and reasoning is important for the organization and management of knowledge

Objectives l l l be familiar with the commonly used knowledge representation and reasoning methods examine the suitability of knowledge representations for specific tasks evaluate the representation methods and reasoning mechanisms employed in computer -based systems

The AI Cycle l l l Almost all AI systems have the following components in general: Perception Learning Knowledge Representation and Reasoning Planning Execution

The AI Cycle

Knowledge and its types l l l what the ‘knowledge’ is? Durkin refers to it as the “Understanding of a subject area”. A well-focused subject area is referred to as a knowledge domain, for example, medical domain, engineering domain, business domain, etc. .

Knowledge and its types l If we analyze the various types of knowledge we use in every day life, we can broadly define knowledge to be one of the following categories:

Knowledge Representation Ø • • • Types of Knowledge Factual Subjective Heuristic Deep or Shallow Other Types

Factual Knowledge l Verifiable n through experiments, formal methods, sometimes commonsense reasoning often created by authoritative sources n l l typically not under dispute in the domain community often incorporated into reference works, textbooks, domain standards

Subjective Knowledge l Relies on individuals n insight, experience l possibly subject to interpretation more difficult to verify l n especially if the individuals possessing the knowledge are not cooperative l different from belief n both are subjective, but beliefs are not verifiable

Heuristic Knowledge l l Based on rules or guidelines that frequently help solving problems often derived from practical experience working in a domain n as opposed to theoretical insights gained from deep thoughts about a topic l verifiable through experiments l Graphs and games like Tic Tac Toe

Deep and Shallow Knowledge l deep knowledge enables explanations and credibility considerations n possibly including formal proofs l shallow knowledge may be sufficient to answer immediate questions, but not for explanations n heuristics are often an example of shallow knowledge Shallow is for time-being consideration while deep is long-term

Other Types of Knowledge l l l l Procedural knowledge Describes how to do things, provides a set of directions of how to perform certain tasks, e. g. , how to drive a car. Declarative knowledge expressed through statements that can be shown to be true or false prototypical example is mathematical logic Tacit knowledge Unconscious knowledge that can be difficult to express in words or other representations

Other Types of Knowledge l Priori knowledge n n independent on experience or empirical evidence General behavior or trend based e. g. “All bachelors are unmarried” l Posteriori knowledge n dependent of experience or empirical evidence e. g. “X was born in 1983” n n

Other Types of Knowledge l Meta knowledge: Knowledge about knowledge, e. g. , the knowledge that blood pressure is more important for diagnosing a medical condition than eye color.

Knowledge and its types Factual Posteriori. Knowledge Tacit Priori. Knowledge Procedural Knowledge Subjective Heuristic Metaknowledge Declarative