TryAgain: The Science, The Math, The Protocols

The imperative Try Again, may be codified, formalized and packaged in a mathematical language, as a science and as precise protocols to assist us in practicing TryAgain efficiently, and to help us create artificial intelligence entities that would use TryAgain to solve the problems before them.

From a mathematical point of view the question is how to best use all the relevant information and all the important lessons learned so far (at the conclusion of the last failed try), in order to practice a best next try.

This challenge is carried out under time constraints: is it better to try again quickly with a good plan devised after a moderate measure of analysis and planning, or to try again later with a likely better plan devised from a longer effort of analysis and planning?

The answer for humans is emotionally charged; the answer for artificial intelligence is based on resource allocation.

Below we present the following topics:

  • Randomness Powered TryAgain

    Randomness is a means to effect changes without wasting effort on planning them, exploiting the power of chance to solve problems and open new vistas. After all, human kind is a case in point for 'randomness in action" as Charles Darwin taught us.

  • TryAgain Dynamics

    Following a failed 'try', it is necessary to allocate resources to an optimal plan between (i) trying again the same as the last try, and (ii) evaluating what to try again and keeping this evaluation until a 'perfect' TryAgain plan is identified. The challenge is to find the optimum between these two extremes.

  • TryAgain Action Template

    The TryAgain Action Template is based on the Fundamental TryAgain Recursion which draws an infinite action map for the purpose of a successful try, of what was tried and failed. The map has three roads: (i) breakdown, (ii) abstraction and (iii) extension.

    Life is a journey of trying again. But what is being tried is in flux. We operate over an array of goals, which we organize as a hierarchy (loose hierarchy at times) in order to establish priorities among the multiplicity of goals we face.

    We model our competing goals as a 'tree' (hierarchy) with a 'root goal' which is parent to children goals which in turn may be parents to their children goals, and so on. Every goal before us fits into this tree (in our model).

    The implications of this model are (i) every goal, except the root has its validity contingent on the validity of its parent goal, and (ii) we go through the life serving a root goal -- which may itself be in flux, but it is always there (whether we see it clearly or not). The second implication leads to the religious aspect of the TryAgain imperative, and first premise is the foundation of the rational mathematical approach to TryAgain.