Smarter Communications as Sign and Cognitive Activity or COGNITIVE SEMIOTICS (CS) - Lecture Course
“Non-Symbol Information Processing” and “Knowledge Management” courses provide a prototype for a formal representation of knowledge processes in Business Process Management (BPM) systems and other kind of intellectual activity.
Their formalisms are implemented as a general framework for a tool for achieving three goals - knowledge description, knowledge processing and knowledge-based decision making -- thus connecting sign and knowledge structures. The tools will help to run an intellectual activity more effectively.
BP Efficiency Improvement. - Business process or any other kind of intellectual activity (BP here in the text) is a complex function of three kinds of human activities – actions in the real world, thinking and sign activity. A car driver turns the steering wheel with his hands, thinks about his next actions to keep on driving, watches the readings on the car’s control devices and on the road and produces signs himself (car lights, turn signals, breaks, etc.). The decisions the driver makes depend upon the same three factors – outer world (reality), signs (semiotic) environment and his own knowledge about driving that resides in his mind. So-called cognitive processes that result in driving decisions remain (up to now) in the driver’s (human) mind only.
There are many ways to improve BP efficiency, to make them smarter. Actually – it is one of IT mainstreams. And semiotic (sign) procedures take an important part in this business. BPs had been described with complex sign systems like UML, ARIS, IDEFs, etc. Then routine parts of BPs execute computers. Creative executions are hard to teach to a computer because they depend upon operations based on knowledge, or so-called ‘cognitive processes.’ Artificial Intelligence (AI) sciences were very successful to describe them and make computers execute them. Still many business process management (BPM) systems include parts that depend upon decisions based on cognitive processes that run in the human mind only. At the same time there are many KM (Knowledge Management) projects that manage to integrate the human knowledge in BP or even make it run on a computer. Their knowledge bases (KB) have been described by ontologies. Cognitive processors (CP) work with them producing new knowledge outside human mind.
But modern databases (DBs) that support BPs are not effective in supporting cognitive processes. “Vlad works on IBM”; “Alex and Vlad work together.” If we store these two facts into any modern DB and ask a question – “Where Alex work?” - few of them will be able to reply – especially without additional adjustments. But it is possible to join Alex and Vlad if their profiles match at a Social Net site. It is a problem of cognitive dialog made upon two sign structures (user profiles). The reason is that there is lack of inference engine (or cognitive processor – CP) in the first case – and quite an effective user profile cognitive processing in the 2nd one.
Both cases look different at first glance. But they can have much in common in their deep or ideal structure. So – there is a well-known lack of effectiveness if we look at the IT products from outside. The problems look different. And we often double our research efforts to resolve them. We need predictive power laws based on simple ideas. Then many IT R&D results will have much in common. Now there are projects that manage to run cognitive processes that produce new knowledge outside of the human mind. They are Semantic Web, Social Net, KM systems, so called Semiotic Web. Actually they connect this or that way sign representations of knowledge (a special kind of KB or ontology) and new knowledge production made by so called agents or other kind of CP.
So – we can connect sign structures (SS) that represent BP realities with knowledge. It is a result of some kind of cognitive process itself. But the second goal is to develop semiotic techniques and procedures that convert them into other SSs that produce new knowledge about BP made by CP (like sometimes unpredictable people connections in Social Net machines). It looks like the sequence of math formulae that solve a problem. This knowledge can be used as a decision support tool for a manager. But the third goal could be declared -- to make this semiotic machine CP decide by itself. The program agent that decides to buy a book at the bookstore Website it plugged into following initial instructions of a customer stored in its KB can be a good example.
There are many partial decisions of this triple goal problem that work in many IT BPM projects. So our main idea and objective is to develop or describe the basic semiotic formalisms that would be able to help in accomplishing these three tasks. Now, if we will be able to treat these SSs as a result of knowledge about connections between BP objects and SSs representing them, then as the basis for reasoning and finally as decision making machine, this cognitive semiotic methodology will help designers in improving BPM systems.
So the knowledge in BPM systems can be described as sign structures (semiotically) and the proposed lecture course is to develop so called Smarter Communications as Sign and Cognitive Activity or Cognitive Semiotics (CS) formalism as a tool to help it and hence to run communications and other kind of BPs more effectively – or even to run them on their own.