Kris Verlaenen [https://community.jboss.org/people/KrisVerlaenen] created the 
discussion

"Re: Process Inference"

To view the discussion, visit: https://community.jboss.org/message/763080#763080

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I think there are different approaches to solving your problem.  Note that some 
of these are still experimental and might not solve exactly what you're looking 
for, but they might at least do something in the same area.

The best researched one is probably "process mining".  This is the idea of 
deriving a process from various information sources, typically some form of 
logs that describe real-life cases (history logs), so those cases can be used 
to automatically create a process based on that, which can then be used for 
future execution.  The downside is that the generated process itself typically 
isn't that flexible (so it might be difficult to deviate).

Ad-hoc processes allow you to specify "recommendations" when executing (a part 
of) a process, and the user can then select which recommendations to execute, 
possibly add new tasks that are not part of the process yet, etc.  This 
typically works well with then using this information (deviations and selected 
recommendation) to improve the process based on this info.

Incomplete processes are processes that don't contain all the logic yet, but 
where parts are left unspecified, and only at runtime will be decided what to 
execute.

Pure Adaptive Case Management (ACM) tries to tackle cases where there is no 
process upfront, people can just create cases and execute these.  It is my 
opinion that these are not a different kind of processes however, but that 
these are just one extreme of processes and that your suggestion is probably 
something in between.  The main idea is that a user has full flexibility here, 
and doesn't need a (full) business process to do his work, but that for example 
recommendations might be generated based on the current state of the case.

We always try to work towards supporting some of these more advanced cases in 
jBPM already.  For example, we do support ad-hoc (sub-)processes and by 
offering users the ability to combine processes with rules and event 
processing, at almost every level, we believe these paradigms combined can also 
allow you to define a lot more flexible yet smart processes.  Integrating for 
example a neural network to support the reasoning would be more experimental, 
we haven't considered this yet at this on its own probably is a big, 
specialized research area.  But if anyone is willing to give it a try, let us 
know, and we'll try to help out where we can !  :) 

Kris
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