Cognition 2.0

During some time my thoughts have been revolving around the concept of information as opposed to that of entropy. Remembering Shannon's book on the Mathematical Theory of Communication, he very clearly lays out the different levels of communication that can be established between two systems:

• Level A. Refers to the accuracy in the transmission process between the sender and the receiver. (The technical problem)
• Level B. Refers to the accuracy in the meaning of the transmitted message. (The semantic problem)
• Level C. Refers to the effectiveness of the transmitted message in the modification of the receiver. (The effectiveness problem)

The technical problem has been the main concern of physicists and mathematicians since the inception of the theory, however the more difficult and also more realistic problems are embedded in the concepts behind levels B and C.

For the purpose of explaining level A and its variations, it is enough to associate information contained in a message with the probability of appearance of every combination of choices between the symbols in a message. This probability is clearly the same as the definition of entropy for a system with N degrees of freedom, where N is the number of symbols in the message. From this point onwards, the theory of information is analogous to the statistical mechanical version of gases and other ergodic systems.

However, information plays a critical role in complex systems, such as in living organisms and cognitive systems. As such, a pure probabilistic theory of information is insufficient to explain and account for phenomena such as heuristics (message interpretation), learning (message storage and abstraction), and generalization (pattern matching and classification). These are only a few examples of basic level B and C type interactions that need to be included in a theory of information that truly represents and explains reality in a living universe.