Intramolecular dynamics. II. Artificial intelligence search evaluation function and treatment of resonance centers for large systems

The role of resonance centers in obtaining large size matrices via an artificial intelligence (AI) search is discussed. The results are used to develop for an AI search an evaluation function which takes cognizance of isolated internal resonances in these many-state systems. The effect of later-accepted states on resonance centers is included. This evaluation function and one without a resonance factor are used in Part III of this series. A search is made there to select zeroth-order vibrational states of benzene that are used in a diagonalization treatment of CH overtone spectra. When there are many overlapping resonances, as in that case, a comparison of results obtained with those two types of evaluation function is of particular interest

Search versus Knowledge: An Empirical Study of Minimax on KRK

This article presents the results of an empirical experiment designed to gain insight into what is the effect of the minimax algorithm on the evaluation function. The experiment’s simulations were performed upon the KRK chess endgame. Our results show that dependencies between evaluations of sibling nodes in a game tree and an abundance of possibilities to commit blunders present in the KRK endgame are not sufficient to explain the success of the minimax principle in practical game-playing as was previously believed. The article shows that minimax in combination with a noisy evaluation function introduces a bias into the backed-up evaluations and argues that this bias is what masked the effectiveness of the minimax in previous studies