AI^Chain

This paper presents a quantitative model to address the accuracy of a blockchain-based decentralized AI Chain along with its performance, referred to as AI<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Chain</sup>. It is hypothesized in this research that the main cause of the inefficacy of conventional AI be the potential bias likely to be caused by the centralized way of decision makings during its execution. The biased centralization is likely to lead to a decision(s) potentially inefficacious thus inaccurate. In this context, a decentralized AI will be presented based on a blockchain-based model. A deterministic decision tree-based AI will be proposed in the context of a blockchain-based decentralized network. The proposed model will employ the baseline chain model [13], which will serve as the probabilistic likelihood for the number of validators to have the transactions and block posting validated accurately. Extensive simulations and results will be presented to demonstrate the efficacy of the proposed model with respect to the average transaction waiting time, the average block capacity required and transaction throughput per block under the influence of average accuracy of the validators and their number.