Which AI Approach is
Best for Helping with Project Planning?Unlike neural networks, expert
systems do not require up-front learning, nor do they necessarily require large
amounts of data to be effective. Yes, expert systems can and do absolutely learn
and get smarter over time (by adjusting or adding rules in the inference engine)
but they have the benefit of not needing to be 'trained up front' in order to
function correctly. Capturing planning knowledge can be a daunting task
and arguably very specific and unique to individual organizations. If all organizations
planned to use the same knowledge, e.g., standard sub-nets, then we could
simply put our heads together as an industry and establish a global 'planning
bible' to which we could all subscribe. This of course isn't the case and so for
a neural network to be effective in helping us in project planning, we would need
to mine an awful lot of data. And, even if we could get our hands on sufficient
data, it probably would not be consistent enough to actually help with pattern
recognition. Neural networks have been described as black boxes — you
feed in inputs, they establish algorithms based on learned patterns and then spit
out an answer. The problem is, they don't tell you why because neural networks
don't understand context! I honestly don't think that as a diligent planning community,
we should rely on a system that doesn't have understanding, or even worse, cannot
explain why a tool comes up with a given answer. The point is that a response
like: "I'm pretty certain you need these activities just because I know" is not
as useful as: "you need these activities based on previous projects X, Y, Z, given
your currently defined scope and the phase of the project you are currently in".
Expert systems tend to excel in environments that are more sequential,
logical and can be 'tamed' by rules. Doesn't that remind you of a CPM network?!
Neural networks pertain more to problems such as recognition through pictures
such as project drawings and BIM.[1] Where
I do believe a neural network approach is useful in a planning tool is in making
the tool smarter. As mentioned, expert systems can get smarter but they need to
be trained. For example, if we can track a planner's reaction to suggestions made
by our expert system, then those reactions can be used to potentially adjust the
weights we give to the various attributes in our expert system. So, referring
back to our original definition of AI, for a useful project-planning tool, we
need an expert system to think and use a neural network to learn. Combine these
two and we have at our disposal, an incredibly powerful planning aid. That is
exactly what we have developed at BASIS.
1.
BIM (Building Information Modeling) is a digital representation of physical and
functional characteristics of a facility. A BIM is a shared knowledge resource
for information about a facility forming a reliable basis for decisions during
its life span: defined as existing from earliest conception to demolition.
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Neural
Networks
