Global Journal of Science Frontier Research, F: Mathematics and Decision Science, Volume 22 Issue 4

© 2022. Edouard Siregar. This research/review article is distributed under the terms of the Attribution-NonCommercial- NoDerivatives 4.0 International (CC BY-NC-ND 4.0). You must give appropriate credit to authors and reference this article if parts of the article are reproduced in any manner. Applicable licensing terms are at https://creativecommons.org/licenses/by-nc- nd/4.0/. Global Journal of Science Frontier Research: F Mathematics and Decision Sciences Volume 22 Issue 4 Version 1.0 Year 2022 Type: Double Blind Peer Reviewed International Research Journal Publisher: Global Journals Online ISSN: 2249-4626 & Print ISSN: 0975-5896 Boosting Human Insight by Cooperative AI: Foundations of Shannon-Neumann Logic By Edouard Siregar Abstract- We present the logical foundation of an artificial intelligence (AI) capable of dealing with (e.g. predicate logic and deep learning). The AI is based on a cooperative questioning game, to boost insight. Insight gains are measured by information, probability, uncertainty (Shannon), as well as utility (von Neumann). The framework is a two-person cooperative iterated Q&A game, in which both players (human, AI agent) benefit (positive-sum): the human player gains insight and the AI player learns to improve its suggestions. Generally speaking, valuable insight is typically gained by asking ’good’ questions about the ’right’ topic, at the ’appropriate’ time and place: by posing insightful questions. In this study, we propose a logical and mathematical framework, for the meanings of ’good, right, appropriate’, within clearly-defined classes of human intentions. Keywords: artificial general intelligence, complexity, cooperative learning games, frame drift problem, information entropy, insight problems, predicate logic, renormalization, utility, value- alignment problem. GJSFR-F Classification: DDC Code: 006.3 LCC Code: Q335 BoostingHumanInsightbyCooperativeAIFoundationsofShannonNeumannLogic Strictly as per the compliance and regulations of: complex dynamic challenges, that would be very hard to handle using traditional approaches