Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Shannon's theory of information stands on a probabilistic representation of events that convey information, e.g., sending messages over a communication channel. Kolmogorov argues that information is a more fundamental concept which exists also in problems with no underlying stochastic model, for instance, the information contained in an algorithm or in the genome. In a classic paper he defines the discrete entropy of a finite set which establishes a combinatorial based definition of the information  I ( x : y ) conveyed by a variable  x (taking a binary string value  x ) about the unknown value of a variable  y . The current paper extends Kolmogorov's definition of information to a more general setting where given ` x =  x ' there may still be uncertainty about the set of possible values of  y . It then establishes a combinatorial based description complexity of  x and introduces a novel concept termed  information width , similar to  n -widths in approximation theory. This forms the basis of new measures of cost and efficiency of information which give rise to a new framework whereby information of any input source, e.g., sample-based, general side-information or a hybrid of both, is represented and computed according to a single common formula. As an application,  consider the space of Boolean functions where input strings  x correspond to descriptions of properties of classes of Boolean functions.
['Joel Ratsaby']
I am writing a research paper on a idea Information Efficiency
[{"from": "human", "value": "I am writing a research paper on a idea Information Efficiency"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Shannon's theory of information stands on a probabilistic representation of events that convey information, e.g., sending messages over a communication channel. Kolmogorov argues that information is a more fundamental concept which exists also in problems with no underlying stochastic model, for instance, the information contained in an algorithm or in the genome. In a classic paper he defines the discrete entropy of a finite set which establishes a combinatorial based definition of the information  I ( x : y ) conveyed by a variable  x (taking a binary string value  x ) about the unknown value of a variable  y . The current paper extends Kolmogorov's definition of information to a more general setting where given ` x =  x ' there may still be uncertainty about the set of possible values of  y . It then establishes a combinatorial based description complexity of  x and introduces a novel concept termed  information width , similar to  n -widths in approximation theory. This forms the basis of new measures of cost and efficiency of information which give rise to a new framework whereby information of any input source, e.g., sample-based, general side-information or a hybrid of both, is represented and computed according to a single common formula. As an application,  consider the space of Boolean functions where input strings  x correspond to descriptions of properties of classes of Boolean functions."}]