Category: Artificial Intelligence

AI as uncertainty management
AI = What to do when you don’t know what to do?
Reasons for uncertainty.
Sensor limits

Definition
-initial state
-action(s) -> {a1, a2, a3 …}
-result(s,a) -> s1
-GoalTest(s) -> T|F
-PATH Cost(s->a -> s ->a ->s)-> n
step cost(s, a, s’) -> n

Tree search

function TREE SEARCH(problem):
	frontier = {[initial]}
	loop:
		if frontier is empty: return FAIL
		path = remove.choice(frontier)
		s = path.end
		if s is a goal: return path
		for a in actions:
			add [path + a -> result(s, a)]
			to frontier

1.Fully versus partially observablez

-perception action cycle
Agent, State
(sensors, actuators)

2.Deterministic versus stochastic

3.Discrete versus continuous

4.Benign(no objective) versus adversarial(such as chess, games)

for example:
robot car -> partially observable, stochastic, continuous, adverial

A AI Program is called
・INTELLIGENT AGENT

how does agent make a decision?
AI has successfully been used in
-finance
-robotics
-games
-medicine
-the web

ex.
trading agent for stock market, bonds market, commodity
->with online news, buy or sell decision

AI in Robotics
camera, microphone, touch
-> motors, voice

AI in games
　game agent play against you. your moves and own moves.

AI in medicine
diagnostic agent get vital signals

AI on the web
crawler