Computers are widely believed to be perfect in carrying these two tasks: computation and communication. They are also expected to be reliable in carrying intelligent tasks like recognition and inference in the future.

From scientific point of view, there are some important remaining challenges for the computers to be faced in not a far future. For example, in computation, computers are still quite weak in solving some important problems like protein folding. In communication, we have not still a well-formed order of information on the Internet and therefore, there are many useful information on the net that would not be accessed properly. In recognition, we have not still a reliable face recognition system at checkpoints.

Facing the above challenges, we should make some drastic changes in our current research approaches in computer science, as the traditional approaches do not seem to achieve the required gain. To this end, we respect the following policies in our research projects:

1. In computation and communication, we follow a coordinative approach in stead of the traditional calculative approach. In the proposed approach, the attribute/functionality of information/processors depends on their physical or logical location. As a good example for the coordinative approach, please consult this short paper from our Appetizer series.

2. In cognition and recognition, we try to establish some models for objectivity, in stead of dealing with the current mathematical models of similarity (such as Bayesian Net, Hidden Markov Model, and Fuzzy Logic). In our proposed models, the behavior of an object is solely depends on its structure. As a sample and primitive model for objectivity, please consult this conference paper from SPIE.

We dub these approaches as the non-traditional computer science, and we expect them to generate some notable advances in the field in both of the theoretical and applied issues. For the people who are interested in philosophy, we should cite that our approaches have their own roots to an ontological viewpoint which is called multiplicity in unit. Among the well-known philosophers who have explained this viewpoint in their works, we can cite these two 17th century philosophers: Molla-Sadra and Leibniz. We also suggest you to read the masterpiece of Leibniz, The Monadology, as a concise explanation of this ontology.



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