First Sponsor Name		 Vince Matsko
First Sponsor Telephone			
First Sponsor E-Mail		vince.matsko@gmail.com
Second Sponsor's Name					
Second Sponsor's Telephone					
Second Sponsor's E-Mail							
Third Sponsor's Name								
Third Sponsor's Telephone								
Third Sponsor's E-Mail										
Staff Liaison 											
Title				Survey of Formal Methods and Artificial Intelligence Systems

Description                     

A vigorous introduction to many areas of Mathematics, Logic,
Philosophy and Computer Science (at the graduate level) intended to
give students a working knowledge of Axiomatic Set Theory,
Meta-mathematics and Mathematical Logic, Proof Theory and Model
Theory, Computational Complexity and Information Theory.  These are
prerequisites to understand the essential material on formal methods
and artificial intelligence from the point of view of Algorithmic
Information Theory (information-theoretic limitations of formal
systems and information-theoretic computational-complexity of
metamathematics) with application to Weak Artificial Intelligence.
The motivation endowed, we will begin to look at how weak A.I. systems
that satisfy the elaborated necessary conditions may be constructed
from public domain software systems.

Prerequisites
(if required)		 

There are no prerequisites except passion for artificial intelligence.
Experience in A.I. and formal methods a plus, as well is knowledge of
GNU/Linux.

Time				
Time slots 			

Morning (8:30-11:30 am)

Afternoon (1:00-4:00 pm)

Evening (6:30-9:30 pm)
	
Minimum Number of Students		1
Maximum Number of Students		20 or more
What will students know and be able to do as part of this session?		 

Students will gain an appreciation of higher mathematics and computer
science and able to solve complex problems in these fields as well as
hold speech with experts.  Students will also be able to construct
weak artificial intelligence systems.

Please provide an overview of daily activities.       

As the ITS (intelligent tutoring systems) technology required to teach
this course in this time-span is not available, we will employ a
satisficing strategy of organic management to satisfy educational
critical success factors.  The goal is to leave the students with an
appreciating and direction for further study and possible
professional collaboration.

In Phase 1 we will have rigorous Mathematics and C.S. instruction akin
to a compressed graduate - postdoctorate level survey course.  Phase 2
will resemble post-doctorate research in open-source Artificial
Intelligence technology.

Common knowledge will be obtained for all prerequisite material before
we progress to considering will attempt to achieve what is called in
A.I. common knowledge on all theorems and concepts of primary
importance.

How do you plan to assess student learning?		 

The goal of the course is to further the human condition through
education and the development of leaders in the field of artificial
intelligence.  As it is not possible to predict who will make the
important breakthroughs, the instructor would prefer not to issue
possibly errant judgments or attempt to quantify in simplistic terms
understanding of inherently complex subjects, as doing so would
violate the very premises of the course.  However, I would follow any
assessment methodology that is recommended.

Estimated cost and proposed source of revenue for activity		 

The materials will be assembled from online open source materials such
as Wikipedia, MIT OpenCourseware, ResearchIndex, etc., therefore there
are no extraneous costs.  A list of books for extra reading will be
provided.

IMSA Resources (equipment, transport, location) requested			 

Classrooms, and possibly computers running GNU/Linux.

Significant commitments or arrangements sponsors would need to consider?