... recent success of Deep Learning, there is renewed hope and interest in Reinforcement Learning (RL)
from the wider applications communities. Indeed, there is a recent burst of new and exciting progress
in both theory and practice of RL. I will describe some results from my own group on a simple new
c ...
... artificial intelligence and far beyond, namely computational complexity,
and in particular, NP-hardness. Hoos will investigate the question to which
extent NP-hard problems are as formidable as is often thought, and present
an overview of several directions of research that aim to characterise and
i ...
... such as neural networks, genetic algorithms, and
fuzzy logic. “Neural,” “fuzzy,” and “genetic” have
been the buzzwords for commercial advertisements
of home appliance makers, such as Samsung, LG, and
Daewoo. Much industrial research in the early 1990s
focused on intelligent control, speech recogniti ...
... suggest? Or how Amazon seems to have your
tastes so figured out? They both use
recommendation systems based on machine
learning which programmatically use people’s
preference data and your behavioral history to
derive increasingly accurate suggestions for you.
Machine learning is especially useful w ...
... One of the other positive developments
in AI since the setbacks of the 1980s involves
the long-running controversy of whether
com-puters should attempt to model how
things are done by humans, known as the
cognitive science approach, or whether they
should follow methods that humans do not
use but th ...
... space. DARPA’s grand challenge for autonomous vehicles was recently won by a Stanford team, with 5 of 23 vehicles completing the
131.2-mile course.2
But AI is not just about robots. It is also
about understanding the nature of intelligent
thought and action using computers as experimental devices. B ...
... • Building intelligent systems to solve problems in the world
⇒ Understanding mechanisms, algorithms, representations for
building intelligent systems
...
... around the possibility of AI.
To pursue this issue, the book starts
by examining the well-known Turing
test as well as discussing some arguments (for example, the argument of
consciousness) against the possibility
of AI that Turing himself addressed
...
... • However, we know this claim to be false, because there
are plenty of machines that do learn. E.g. there are
machines that learn to play chess, learn to walk, learn to
diagnose diseases, etc.
• Again, we only look at the machine from the underlying
mechanical/programming point of view. Yes, the
mac ...
... Course Objectives: Artificial Intelligence (AI) is viewed in different ways, which makes it hard
to define in a precise way. However, a majority of computer scientists, engineers, and cognitive
psychologists view AI as a discipline that enumerates and explores tasks that are hard and computationally ...
... As a matter of fact I believe this IIM will be exceptionally good for advancing these abilities.
As an interdisciplinary study it requires one to examine a single problem from multiple
perspectives. Furthermore, it takes discipline, rational thinking, and thoroughness to engage in
scientific thinkin ...
... • Out of the 4 types of economic systems that exist
today, most of them have some or the other
disadvantage and all the economic structures
deployed have seen a phase where economy has
plummeted at some point in time.
• So it’ll be notably interesting to see how our economic
future with highly advan ...
... F. ___D____ to define secondary content that might appear in a sidebar
G. __F___ to define images that annotate an article
15. Both Java Applets and Java Server pages (JSP) are embedded in what type of document
that is executed in a browser?
...
... Turing test: how can we decide if something is intelligent?
Traditional (symbolic) AI
early programs, and knowledge representation and search
GPS, microworlds, expert systems
Chinese room
Functionalists: thought is symbol manipulation
Searle and Chinese room – computers can manipulate symbols, but
t ...
... be an immoral science. The reason for this is simple: it is – how shall I
put it? – a purely grammatical matter.
If the premises of a syllogism are both in the indicative, then the
conclusion will equally be in the indicative. In order for a conclusion to
be able to be taken as an imperative, at lea ...
... indeed stand as a compelling existence proof that
machine intelligence should be possible. Unless
you ascribe some sort of magical, religious, or
quantum-dynamical “soul” to people (and, perhaps even more strangely, you deny such a thing
to computers).
Sometimes this analogy is useful: we can be
ins ...
... – A priori knowledge: Previous knowledge that does not get modified
with new experiences
– Statistical information extracted from the patterns
– Example: Face recognition system – understanding pixels
...
... performed. If there are too few chromosomes, GAs have few
possibilities to perform crossover and only a small part of search
space is explored. On the other hand, if there are too many
chromosomes, GA slow down. Crossover probability is usually
beetween 0.4 and 0.7.
Mutation probability ( Pm ): how ...
... will have become a normal stage of life. Almost everyone will expect to
survive it, and this mass belief will make it so.
The biological incarnation of human beings, if it is still necessary, would
be viewed the way intelligent amphibians might view tadpoles, as a “larval”
phase of human existence. ...
... • AI is a collection of hard problems which can be
solved by humans and other living things, but for
which we don’t have good algorithmic solutions
– e.g., understanding spoken natural language, medical
diagnosis, circuit design
...
... infancy. The problem of controlling intelligent machines is just now being recognized36 as a
serious concern and many researchers are still skeptical about its very premise. Worse yet, only
about 100 people around the world are fully emerged in working on addressing the current
limitations in our un ...
The philosophy of artificial intelligence attempts to answer such questions as: Can a machine act intelligently? Can it solve any problem that a person would solve by thinking? Are human intelligence and machine intelligence the same? Is the human brain essentially a computer? Can a machine have a mind, mental states and consciousness in the same sense humans do? Can it feel how things are?These three questions reflect the divergent interests of AI researchers, cognitive scientists and philosophers respectively. The scientific answers to these questions depend on the definition of ""intelligence"" and ""consciousness"" and exactly which ""machines"" are under discussion.Important propositions in the philosophy of AI include:Turing's ""polite convention"": If a machine behaves as intelligently as a human being, then it is as intelligent as a human being. The Dartmouth proposal: ""Every aspect of learning or any other feature of intelligence can be so precisely described that a machine can be made to simulate it."" Newell and Simon's physical symbol system hypothesis: ""A physical symbol system has the necessary and sufficient means of general intelligent action."" Searle's strong AI hypothesis: ""The appropriately programmed computer with the right inputs and outputs would thereby have a mind in exactly the same sense human beings have minds."" Hobbes' mechanism: ""Reason is nothing but reckoning.""↑ ↑ ↑ ↑ ↑ ↑
