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Chapter 4 Annotation language for trains
4.2 Reasoning model
The simplest form of artificial intelligence (AI) which is generally used in
industry is the rule-based system, also known as the expert system. Before we
discuss in details what these are, let's take a step back and point out that there are
different opinions as to what really constitutes artificial intelligence. Some
people, when they use the term AI, are referring to systems which have some
ability to learn. That is, the system will improve its performance over time as it
gains experience in solving problems, just as a human would. Others, when they
use the term AI, are referring just to systems which are capable of exhibiting
human-level performance in some very narrow area, but which are incapable of
learning or expanding their expertise.
Different people are always going to disagree about what AI is, but this is fairly
simple form of AI which we want to discuss about right now. A rule-based
system is a way of encoding a human expert's knowledge in a fairly narrow area
into an automated system. There are a couple of advantages to doing so. One is
that the human expert's knowledge then becomes available to a very large range
of people. Another advantage is that if you can capture the expertise of an expert
in a field, then any knowledge which they might have is not lost when they retire
or leave the firm. Rule-based systems differ from standard procedural or objectoriented programs in that there is no clear order in which code executes. Instead,
the knowledge of the expert is captured in a set of rules, each of which encodes a
small piece of the expert's knowledge. Each rule has a left hand side and a right
hand side. The left hand side contains information about certain facts and objects
which must be true in order for the rule to potentially fire (that is, execute). Any
rules whose left hand side match in this manner at a given time are placed on an
agenda. One of the rules on the agenda is picked (there is no way of predicting
which one), and right hand side is executed, and then it is removed from the
agenda. The agenda is then updated (generally using a special algorithm called
the Rete algorithm (Appendix C)), and new rules are selected to execute. This
continues until there are no more rules on the agenda.
Another reasoning model we can use is BDI agents, BDI stands for BeliefDesire-Intention [35]. A BDI agent is a particular type of bounded rational
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Video content analysis & aggression detection system for a train environment