BUSS 315: Knowledge-Based Information Systems
Department of Information
Systems, University of Wollongong
Lecture content outlines and pointers to web resources:
A brief outline of each lecture completed thus far is provided below.
Links to related web resources relevant to each
lecture as well as readings on business applications of the
technology discussed in each lecture are also provided.
- Lecture 1: We looked at definitions of AI/KBS's, the history of the
area, major milestones and outlines of the major sub-areas. The Association for Computing Machinery
(ACM) Special Interest Group on Artificial Intelligence (SIGART)
directory of web resources on AI is a great place to start
exploring. The ACM is the oldest and
largest association of computing professionals in the world, and its
homepage is worth looking at. The SIGART
homepage contains other interesting information, including a pointer
to the SIGART Bulletin which contains good survey articles, as well
announcements of new conferences/seminars.
- Lecture 2: We looked at the basic elements of an agent architecture
and discussed a variety of application domains. We talked about the
Turing Test for AI, and as promised, this is a pointer to
a fun contest where programs compete to win the Turing Test for true AI.
In the labs, we discussed the architecture of the MYCIN expert system
and looked
at a transcript of a session with MYCIN. You can download a variety of
interesting AI software from the Carnegie Mellon University AI Repository.
- Lecture 3: We looked at the general notion of search through a
state space as a common theme underlying most AI problem solving. We
considered blind search technqiues such as depth-first (DFS),
breadth-first
(BFS) and iterative deepening search (this link provides a demo of what
happens when depth-first search is applied to the problem of solving the
8-puzzle, while this link
provides applet-based demos of both DFS and BFS).
- Lecture 4: We looked at heuristic search techniques such as
best-first search and A* search (this link applies A* search to the 8-puzzle). We also
looked at hill climbing and related techniques. The BOTSPOT site has interesting information on agent
applications.
- Lecture 5: We looked at how search techniques can be used to solve
constraint satisfaction problems. Several companies sell constraint
solving (or constraint programming) software that
can be used to solve difficult optimization problems. These include ILOG and COSYTEC. This link
contains several papers on how constraint programming techniques can be
used to solve real business problems.
- Lecture 6: We looked at reasoning with propositional logic.
You can try
out all of what we have done with propositional logic using this
interactive web-based propositional theorem prover developed by the
Information Systems group at the University of Newcastle - the system
is called VADER and you can access it by clicking here.
- Lecture 7: We discussed first-order logic.
- Lecture 8: We discussed natural deduction inference in first-order
logic (using rules of inference such as Modus Ponens). We also discussed
the Generalized Modus Ponens rule and its application in forward and
backward chaining inference.
- Lecture 9: We discussed resolution theorem proving in first-order
logic.
- Lecture 10: We discussed reasoning about actions and planning using
the situation calculus.