What is AI? - TAMU Computer Science Faculty Pages

geographertonguesAI and Robotics

Nov 30, 2013 (3 years and 8 months ago)

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What is Artificial Intelligence?


not

programming in LISP or Prolog (!)


depends on your perspective...


a method for modeling intelligence


a method for studying human cognition


a method for building complex programs


Answer from a Philosopher
: a method for
modeling
intelligence


How do you define “intelligence”?


ideal: syllogisms...laws of thought...logic


need for embodiment? mind
-
body duality (Descartes)


physical brain required? Chinese Room experiment


Symbol Systems Hypothesis (Simon and Newell)


grounding, mechanization, novelty, adaptiveness,


animals? souls? free will?


operational definition: acting intelligent


Turing test; what is the correct measuring stick?


no contact, response characteristics, news, humor, gender...


Eliza, chatter bots, Loebner prize, Deep Blue


Answer from a Psychologist
: a method for studying
human cognition


strengths:


perception, ambiguity, interpretation


ill
-
formed problems; weighing multiple criteria


judgement, common
-
sense,
expertise


“insight”, analogy, Eureka effect


weaknesses:


calculations


limited, selective, and maleable memory


confirmation bias; role of emotions?


behaviorism vs. info
-
processing metaphor (I/O, internal rep)


connection to language



Sapir
-
Whorf hypothesis (verbal representations)


concepts, intension/meaning, maps, skills, automation


Answer from an Engineer
: a method for
building complex programs


need more than just C++ or java (or OOP)


search algorithms, inference techniques,
methods for dealing with uncertainty...


knowledge
-
based programming


Feigenbaum: “In the knowledge is the power”


high
-
level programming languages, expressiveness


expert systems, logic, McCarthy


real
-
world knowledge bases, ontologies, Cyc


intelligent agents: decision
-
making


control theory, “cybernetics,” Kalman filters


decision theory: Bayes, Markov


Relationships of AI to other fields:


Economics


rational decision
-
making; satisficing (Simon)


Mathematics


computability; Godel’s Incompleteness Theorem;
logic and number theory; Leibnitz


Neuroscience


neural networks, Minsky


connectionism, distributed representations,
grounding