By Sophie Dulhunty at October 11 2018 17:28:21
All process instances are executed in a very similar way and it is easy to draw a flowchart detailing the sequence in which tasks are executed. It is also possible to formalize the business rules that guide decisions, normally based on the evaluation of some process variables. But recently other kinds of processes have caught the attention of process management specialists. They are known as knowledge processes, or knowledge-based processes. Knowledge processes can be defined as "high added value processes in which the achievement of goals is highly dependent on the skills, knowledge and experience of the people carrying them out". Some examples could be management, R&D, or new product development processes.
Here are the types of evidence you can use: Images ; A photo is often a great way to show a point. You can use a photo in three ways: * Literally: If you're talking about a piece of equipment, show a photo of it rather than describe its specifications in bulleted text. You can use callouts that point to the various features and label them. * Metaphorically: Sometimes a point you're making is a concept, rather than a fact. For example, you may be talking about tough times ahead, so you could show a photo of a rocky road or a steep staircase. * Schematically: If you're talking about a process, you can show it with a diagram or add arrows to point out parts of a photo.
In the last few years a lot has been written about Business Process Management, and about technologies supporting it such as BPMS, SOAP and Web Services. Most of these theories, tools and techniques refer to processes of a highly structured nature. Typically, BPM theorists and practitioners have focused on highly structured processes, like back-office processes of industrial or administrative nature. These processes are highly standardized and repeatable, produce a consistent output and are likely to be automated in part or end-to-end (STP).
The possibility of developing some such artifact has intrigued human beings since ancient times. With the growth of modern science, the search for AI has taken two major directions: psychological and physiological research into the nature of human thought, and the technological development of increasingly sophisticated computing systems. In the latter sense, the term AI has been applied to computer systems and programs capable of performing tasks more complex than straightforward programming, although still far from the realm of actual thought. The most important fields of research in this area are information processing, pattern recognition, game-playing computers, and applied fields such as medical diagnosis.