Martin: Created page with "=Terminology= ;Intelligent Agent : Interacts with environment Sensors -> Control Policy -> Actuators = '''Perception Action Cycle''' ;Fully Observable : Sufficient informati..."

2021-09-14T21:43:29Z

Created page with "=Terminology= ;Intelligent Agent : Interacts with environment Sensors -> Control Policy -> Actuators = '''Perception Action Cycle''' ;Fully Observable : Sufficient informati..."

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=Terminology=

;Intelligent Agent
: Interacts with environment
Sensors -> Control Policy -> Actuators = '''Perception Action Cycle'''

;Fully Observable
: Sufficient information to make optimal decision
;Partially Observable
: Memory required on agent - not all information available

;Deterministic
: Agents actions uniquely determine outcome
;Stochastic
: Outcomes include randomness - not wholly predicted by action e.g. dice game

;Discrete
: Finite number of sense/actions e.g. chess
: Continuous - Infinite number of sense/actions e.g. darts

;Benign
: No others have objective that is contra to your objective e.g. weather
;Adversal
: They are out to get you - e.g. Chess

{| class="wikitable" border="1" cellspacing="0" cellpadding="5"
|-
! Activity !! Fully Observable !! Stocastic !! Discrete !! Adversal
|-
| Chess || Y || N (Determined by Agent + Opponent) || Y || Y
|-
| Poker || N || Y || Y || Y
|-
| Robotic car || N || Y || N || N (Not in Stanford)
|}

=Rationality=
Does the "right" thing given what it knows

==Uncertainty management in software==
What to do when you don't "know"
* Causes - Sensor limits, Adversary, Laziness (could compute - e.g. too expensive), Ignorant - could know but don't care to know

=Problem Solving=
# Initial state
# Action(State) -> {a1, a2, a3...} - actions from set may be dependent on state
# Result(State, Action) -> S' - new state
# GoalTest(State) -> True/False - reached goal
# <nowiki>PathCost(S -a1-> S' -a2-> S''...) = n - cost of step, action combinations</nowiki>
# StepCost(S, a, S') = n - Most path costs can be considered additive thus this can be considered the sum of a StepCost

=Admissible heuristics=
heuristic must be optimistic
* h(s) < true cost

=Problem solving requirements=
* fully observable
* known domain - actions available
* discrete domain - finite
* deterministic
* static - nothing else changes world other than our actions

=Turing Test=
Requires:
* natural language processing
* knowledge representation
* automated reasoning
* machine learning
Full Turing test also:
* computer vision
* robotics

=Syllogisms=
* logical reasoned arguments

Logic solving systems exist but modelling a problem 100% logic and resources required are limiting factors in using this

Artificial Intelligence Terminology - Revision history

Martin: Created page with "=Terminology= ;Intelligent Agent : Interacts with environment Sensors -> Control Policy -> Actuators = '''Perception Action Cycle''' ;Fully Observable : Sufficient informati..."