csci 4410 introduction to artificial intelligence
Post on 27-Dec-2015
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What is AI?
Difficult to define “The Intelligence of a System is
inversely proportional to our understanding of it”
What is AI? making computer programs that appear to think?
the automation of activities we associate with human thinking, like decision making, learning ?
the art of creating machines that perform functions that require intelligence when performed by people ?
the study of mental faculties through the use of computational models ?
the study of computations that make it possible to perceive, reason and act ?
a branch of computer science that is concerned with the automation of intelligent behavior ?
anything in Computing Science that we don't yet know how to do properly ?
AI
“The art of creating machines that perform functions that require intelligence when performed by people.” (Kurzweil)
“The study of how to make computers do things at which, at the moment, people are better.” (Rich and Knight)
But what about creativity? Many would argue
machines are already writing rap music and reality shows
Rational Systems
How do we know how humans think? Introspection vs. psychological
experiments Brain research (scanning,
experiments, testing) Cognitive Science
Rational Systems
Humans are not always ‘rational’ Rational - defined in terms of
logic? Logic can’t express everything
(e.g. uncertainty) Logical approach is often not
feasible in terms of computation time - needs ‘guidance’
We will never get to intelligence with rules
Satisfiability
Rule systems must be checked This is the Satisfiability Problem NP-complete Checking all the states of a large
rule system is computationally expensive
Turing Test
Described by Alan Turing in 1950 A human judge engages in a
natural language conversation with a human and a machine
If the judge cannot reliably tell which is which, then the machine passes the Turing test.
The conversation is usually limited to text.
Turing Test
A machine passing the Turing test may be able to simulate human conversation
Is this intelligence? how do we know humans don't
just follow rules? Blockhead – all paths Chinese room - rules
Can young children pass the test?
Turing Test
Turing test measures human-like behavior
Even if the Turing test is a good definition of intelligence, it may not indicate consciousness.
Does intelligence imply consciousness?
Practical AI
Do we care whether a system:Replicates human thought
processesMakes the same decisions as
humansUses purely logical reasoning
AI in Practice Medical advice system
Part-picking robots
Credit card fraud detection
Spam filters
Medical diagnosis, teleoperated/micro surgery
AI in Practice
Information retrieval, Google
Scheduling, logistics, supply chain management
Aircraft and pipeline inspection
Speech recognition, generation, translation
AI in Practice
And robots and chatbots
Heuristics
Two fundamental goals: finding algorithms with good run
times and optimal solutions.
But… these goals are often mutually exclusive
A heuristic is an algorithm that relaxes one or both of these goals
Heuristics
Special instances of the problem may cause the heuristic to produce poor results or run slowly
These instances may be rare Ex: sorting algorithms where the list
is already sorted Matching the heuristic to the
domain is important Heuristics are very common in
real world implementations.
Example – Spam Assassin Spam Assassin uses a wide variety of heuristic
rules to determine whether an email is a spam or ham Bayesian filter Blacklisting Regular expression matching
Modern Focus
Artificial intelligence can be considered under a number of headings: Search Representing Knowledge and
Reasoning Planning Uncertainty Learning Interacting with the Environment
(e.g. Vision, Speech, Robotics)
Search Search is the fundamental technique of AI.
Possible answers, decisions or courses of action are structured into an abstract space, which we then search.
Search is either "blind" or "informed": blind
we move through the space without worrying about what is coming next, but recognising the answer if we see it
informed we guess what is ahead, and use that
information to decide where to look next.
Desire for optimal solutions leads to heuristics
Knowledge Representation and Reasoning If we are going to act rationally in our environment,
then we must have some way of describing that environment. how do we represent what we know about the
world ?
how do we represent it concisely ?
how do we represent it so that we can get hold of the right piece of knowledge when we need it ?
how do we generate new pieces of knowledge ?
how do we deal with uncertain knowledge ?
Planning
Given a set of goals, construct a sequence of actions that achieves those goals:
often very large search space but most parts of the world are
independent of most other parts often start with goals and connect them
to actions no necessary connection between order
of planning and order of execution what happens if the world changes as we
execute the plan and/or our actions don’t produce the expected results?
Uncertainty
Given the set of “uncertain” information, how can we achieve the goals (and how certain are we of that answer).
How do we deal with uncertainty in our daily lives?
How can we make this more systematic How can we build systems that deal with
uncertainty How can we insure that the systems are
reasonable and correct
Learning If a system is going to act truly
appropriately, then it must be able to change its actions in the light of experience:
Generating new facts from old
How do we generate new concepts ?
How do we learn to distinguish different situations in new environments ?
Knowledge
Virtually all techniques benefit from ‘common sense’
CYC – a very large database of general purpose knowledge
Resolving Ambiguity – Ex. Consider the following pair of sentences:
Fred saw the plane flying over Zurich. Fred saw the mountains flying over Zurich.
Humans recognize that in the first sentence, "flying" refers to the plane
In the second sentence, "flying" almost certainly refers to Fred.
Traditional Natural Language systems will have difficulty resolving this syntactic ambiguity
Cyc knows that planes fly and mountains do not, and can reject nonsensical interpretations.
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