Meta-Cognitive Problem-Solving: a Systematic Framework for Problem-Solving Verification

EasyChair Preprint 15777

Abstract

Computational problem-solving is often inefficient in terms of effective verification processes, introducing potential inaccuracies in problem-solving approaches. In this work, meta-cognitive methods for systematic problem-solving with an emphasis on constraint realization, invariant property analysis, and solution verification have been examined. Drawing from recent advances in AI metacognition and cognitive problem-solving frameworks, we present the importance of systematic problem-solving protocols in excluding cognitive biases and unverified statement claims for a correct solution.

Keyphrases: AI verification, Constraint Analysis, Meta-cognitive problem-solving, systematic reasoning.

@booklet{EasyChair:15777,
  author    = {Mohamed Abbas},
  title     = {Meta-Cognitive Problem-Solving: a Systematic Framework for Problem-Solving Verification},
  howpublished = {EasyChair Preprint 15777},
  year      = {EasyChair, 2025}}