Designing biochemical systems that can be effectively used in diverse fields, including diagnostics, molecular computing and nanomachines, has long been recognized as an important goal of molecular programming and DNA nanotechnology. A key issue in the development of such practical devices on the nanoscale lies in the development of biochemical components with information-processing capacity. In this article, we propose a molecular device that utilizes DNA strand displacement networks and allows interactive inhibition between two input signals; thus, it is termed a cross-inhibitor. More specifically, the device supplies each input signal with a processor such that the processing of one input signal will interdict the signal of the other. Biochemical experiments are conducted to analyze the interdiction performance with regard to effectiveness, stability and controllability. To illustrate its feasibility, a biochemical framework grounded in this mechanism is presented to determine the winner of a tic-tac-toe game. Our results highlight the potential for DNA strand displacement cascades to act as signal controllers and event triggers to endow molecular systems with the capability of controlling and detecting events and signals.

A deeper game-tree search can yield a higher decision quality in a heuristic minimax algorithm. However, exceptions can occur as a result of pathological nodes, which are considered to exist in all game trees and can cause a deeper game-tree search, resulting in worse play. To reduce the impact of pathological nodes on the search quality, we propose an iterative optimal minimax (IOM) algorithm by optimizing the backup rule of the classic minimax algorithm. The main idea is that calculating the state values of the intermediate nodes involves not only the static evaluation function involved but also a search into the future, where the latter is given a higher weight. We experimentally demonstrated that the proposed IOM algorithm improved game-playing performance compared to the existing algorithms.