Game Theory in Molecular Nanosensing System for Rapid Detection of Hg2+ in Aqueous Solutions

Game theory—the scientific study of interactive, rational decision making—describes the interaction of two or more players from macroscopic organisms to microscopic cellular and subcellular levels. Life based on molecules is the highest and most complex expression of molecular interactions. However, using simple molecules to expand game theory for molecular decision-making remains challenging. Herein, we demonstrate a proof-of-concept molecular game-theoretical system (molecular prisoner’s dilemma) that relies on formation of the thymine–Hg2+–thymine hairpin structure specifically induced by Hg2+ and fluorescence quenching and molecular adsorption capacities of cobalt oxyhydroxide (CoOOH) nanosheets, resulting in fluorescence intensity and distribution change of polythymine oligonucleotide 33-repeat thymines (T33). The “bait” molecule, T33, interacted with two molecular players, CoOOH and Hg2+, in different states (absence = silence and presence = betrayal), regarded as strategies. We created conflicts (sharing or self-interest) of fluorescence distribution of T33, quantifiable in a 2 × 2 payoff matrix. In addition, the molecular game-theoretical-system based on T33 and CoOOH was used for sensing Hg2+ over the range of 20 to 600 nM with the detection limit of 7.94 nM (3σ) and for determination of Hg2+ in pond water. Inspired by the proof-of-concept for molecular game theory, various molecular decision-making systems could be developed, which would help promote molecular information processing and generating novel molecular intelligent decision systems for environmental monitoring and molecular diagnosis and therapy.

Regression-Based Approach For Feature Selection In Classification Issues. Application To Breast Cancer Detection And Recurrence

Feature selection is considered a key factor in classifications/decision problems. It is currently used in designing intelligent decision systems to choose the best features which allow the best performance. This paper proposes a regression-based approach to select the most important predictors to significantly increase the classification performance. Application to breast cancer detection and recurrence using publically available datasets proved the efficiency of this technique.

AI TOOLS IN DECISION MAKING SUPPORT SYSTEMS: A REVIEW

AI tools have advanced sufficiently such that they are integrated into decision making support systems for real applications and are impacting decision making in substantive ways. This paper reviews decision making theories and AI tools and the intelligent decision systems that result from the integration of these concepts.

Employing Intelligent Decision Systems to Aid in Information Technology Project Status Decisions

When a firm initiates and invests into an information technology (IT) project, it is usually with the intention of realizing benefits in the informational, strategic, transactional, and infrastructure objective areas of its IT portfolio (Weill & Broadbent, 1998). From the project management perspective, it is critical to know how the project is performing from the viewpoint of scope, schedule, cost, and other constraints. Lewis (2008) reports that 70% of IT-related projects do not meet their objective. This chapter examines the use of a case-based reasoning decision support architecture that provides a collaborative intelligent agent system to aid in recommending the status of a project using color indicators (Red, Yellow, Green) derived from the progress and condition of the project-related constraints.