Predictive heuristics for solving AGI architecture decision-making problems

Algorithmic or Heuristic Problem-Solving Method

This study explores the problem surrounding the learners of AGI architecture within reference to decision making capabilities for the real world operation. While the operation of the AGI architecture can be applicable within a real world environment, however, few applicable methodologies and theories support its functionalities. Due to the inherent time-constraint, a direct application to the decision-making theory is not applicable. This study presents the predictive heuristics theory to solve the problem.

Objective of this paper is to use the heuristic theoretical framework to solve the problem posed by the application of AGI system, which is inherent with the time constraints.

Heuristic Application to solve the AGI System Application

In the contemporary environment, human problems are in a large scale where the decision-making procedures are subject to time constraints. One of these problems is the application of AGI architecture where decision is time constraint. The resources and decision theoretical framework fail to address this type of stochastic nature, thus, the predictive heuristic is a viable solution to the decision-making problems posed by the AGI architecture. The heuristics are defined as strategies of using readily accessible, loosely applicable, and information resources to solve human and machine problems. (Helgason, Thorisson, Nivel, et al. 2011).

Fig 1: AGI System Search Problem

The fig 1 reveals the typical AGI architecture problem that provides the tree structure where each level corresponds atomic moment of time. Where a) represents moment of time, b) represent the T1 (next moment of time) and S0 enumerates possible future state from S1, 0 to S1, n. All the states are used to evaluate the heuristic utility functions. The d) reveals the comparison of the utility value and the results reveals the expansion evaluated state.

Conclusion

In the contemporary environment, some problems can be solved using systematic instructions based on the algorithms technique. For example, it is possible for a professional librarian to assemble a new bookcase following directions of assembly, which comes with a new package. By using the Pythagorean Theorem, it is possible to arrive at a correct solution by following the algorithms steps. Despite the benefits that algorithms provides, the world situation sometimes present many problems that no algorithms is able to solve. For example, no rules exist to follow in order to address a destruction of rain forest. Moreover, no rule to follow to identify a metal ship substitute. In this scenario, it is critical to use a heuristic. This paper demonstrates the strategy that can be employed in solving the problem of AIG architecture characterized by the time constraints. The paper uses the heuristic method to solve the problems because the algorithms is unable to address the problems based on its time constraints features.

Reference

Helgason, H.P. Thorisson, K.R. Nivel, E. et al. (2011). Predictive Heuristics for Decision-Making in Real-World Environments. Artificial General Intelligence. 7999: 50-59.

Ormrod, J.E. (2008). Educational Psychology Developing Learners. Pearson Education Inc.