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moscow[e87,jmc]		Non-monotonic reasoning and causality

Notes:

Artificial intelligence research has led us to philosophical
conclusions.  Here are some.

1. Languages of mathematical logic are appropriate for representing
what an AI system knows about the common sense world.  There are
no serious competitors at present.

2. Logical deduction requires extension by formalized non-monotonic reasoning.

3. Formalization of contexts may also be required.

4. Epistemology can be made mathematical by developing a mathematical
meta-epistemology which studies the relation between a world and
a knowledge-seeker in the world.  What a knowledge seeker can learn
about the world depends on the structure of the world, the seeker's
opportunities for observation and action, what the seeker admits as
meaningful statements about the world, what the seeker accepts as
evidence and what assumptions are built in to the seeker's program.



meta-epistemology, cartesian counterfactuals, approximate theories,
logical treatment of common sense knowledge, formalization of contexts.

Slides:

non-monotonic formula, informal example,

slogans

informal example of causality

logic and common sense

examples of common sense assertions requiring formal expression

Russell says that as science advanced, causality sentences became
unnecessary.  However, consider the Nemesis theory of mass extinctions.

``All philosophers, of every school, imagine that causation is one
of the fundamental axioms or postulates of science, yet, oddly enough,
in advanced sciences such as gravitational astronomy, the word `cause'
never occurs ...''
 The law of causality, I believe, like much that passes
muster among philosophers, is a relic of a bygone age, surviving, like the
monarchy, only because it is erroneously supposed to do no harm ..."

Causality statements are made in certain kinds of information situations.