Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Knowledge based systems -- introduction
1. Knowledge-Based Systems:
Introduction
Richard Dybowski
5 Feb 2008
Russell & Norvig (2003), Chapter 1
2. Aims
● To understand the concept of AI in terms
of a rational agent
● To appreciate AI's history and ability
3. Artificial Intelligence (AI)
AI attempts not just to understand how we think but
also to build intelligent entities by attempting to
systemise and automate intellectual tasks.
AI encompasses many subjects from general-
purpose areas, such as learning and perception, to
specific tasks such as playing chess and
diagnosing diseases.
5. “But what exactly is AI?”
There are different answers
to this question (depending
on who you ask)
6. Russell & Norvig (2003) classification of eight AI
definitions:
A rational system does the “right thing”
given what it knows
7. The “rational agent” approach
Best approach because:
(a) More general than “laws of thought approach”
because rationality is not only about correct inference
(b) More amenable to scientific development than
approaches based on human behaviour or human
thought
8. History of AI
Gestation (1943 – 1955):
McCulloc & Pitts (1943) – artificial neurons
Hebbian learning (1949)
Turing test (1950)
Birth of AI (1956):
1956 Workshop at Dartmouth College
Early enthusiasm (1952-1969):
Many limited successes; e.g., General Theorem Prover,
LISP, microworld problem solvers
9. History of AI (continued)
A dose of reality (1966 – 1973):
Early systems failed on more difficult problems
Knowledge-based systems (1969 – present):
DENDRAL (1099); MYCIN (1980); etc
AI becomes an industry (1980 - present):
R1 (1982) - first commercial expert system
but followed by “AI Winter”
Return of neural networks (1986 - present):
Back-propagation building algorithm (1986)
10. History of AI (continued)
AI becomes a science (1987 – present):
● Scientific method adopted
● Common to build on existing theories
● Claims based on rigorous theorems or hard
experimental evidence
● Relevant to real-world applications
The emergence of intelligent agents (1995 – present):
“Bots” on the Internet
11. The state of the art
What can AI do today?
Examples:
● Machine planning; e.g. NASA's Remote Agent (2000) –
monitors spacecraft operations
● IBM's Deep Blue (1997) – beat Kasparov
● Lymphatic cancer diagnosis (1991) – beat an expert!
