Innovative idea generation in problem finding: Abductive reasoning, cognitive impediments and the promise of Artificial Intelligence

2021 ◽  
Author(s):  
Massimo Garbuio ◽  
Nidthida Lin
Keyword(s):  
Artificial Intelligence ◽  
Idea Generation ◽  
Abductive Reasoning ◽  
Problem Finding ◽  
Innovative Idea

scholarly journals Towards Trustable Explainable AI

2020 ◽  
Author(s):  
Alexey Ignatiev
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Recent Work ◽  
Abductive Reasoning ◽  
Rigorous Approach ◽  
Explainable Artificial Intelligence ◽  
Explainable Ai ◽  
Close Relationship

Explainable artificial intelligence (XAI) represents arguably one of the most crucial challenges being faced by the area of AI these days. Although the majority of approaches to XAI are of heuristic nature, recent work proposed the use of abductive reasoning to computing provably correct explanations for machine learning (ML) predictions. The proposed rigorous approach was shown to be useful not only for computing trustable explanations but also for validating explanations computed heuristically. It was also applied to uncover a close relationship between XAI and verification of ML models. This paper overviews the advances of the rigorous logic-based approach to XAI and argues that it is indispensable if trustable XAI is of concern.

scholarly journals Does Power Distance Necessarily Hinder Individual Innovation? A Moderated-Mediation Model

2020 ◽  
Vol 12 (6) ◽  
pp. 2526
Author(s):  
Shiwen Luo ◽  
Jie Wang ◽  
David Yoon Kin Tong
Keyword(s):  
Sustainable Development ◽  
Power Distance ◽  
Idea Generation ◽  
Task Characteristics ◽  
Mediation Model ◽  
Voice Behavior ◽  
Moderated Mediation Model ◽  
Innovative Idea ◽  
The Relationship ◽  
Innovation Behavior

Individual innovation behavior is the driving force for enterprise sustainable development and can be affected by many factors, among which power distance is important. To explore the mediating mechanism and boundary conditions of power distance on individual innovation behavior, this paper constructed a moderated mediation model with task characteristics as the moderator and voice behavior as the mediator from the two-dimensional perspective of individual innovation behavior (innovative idea generation and implementation). Responses to 336 valid questionnaires from 133 technological innovation enterprises in China revealed that power distance has a negative effect on innovative idea generation, but a positive effect on innovative idea implementation. In this process, task characteristics only play a moderating effect in the relationship between power distance and innovative idea implementation, but fail to moderate the relationship between power distance and innovative idea generation. In addition, it was found that voice behavior mediates the relationship between power distance and individual innovation behavior. This study provides useful insight on the mechanism of organizational culture on individual innovation behavior, and suggests leaders take effective measures to improve the enterprise sustainable development ability.

scholarly journals Prime Implicates and Prime Implicants: From Propositional to Modal Logic

2009 ◽  
Vol 36 ◽  
pp. 71-128 ◽  
Author(s):  
M. Bienvenu
Keyword(s):  
Artificial Intelligence ◽  
Modal Logic ◽  
Propositional Logic ◽  
Description Logic ◽  
Recognition Task ◽  
Abductive Reasoning ◽  
Upper And Lower Bounds ◽  
Knowledge Compilation ◽  
Prime Implicants ◽  
Computational Properties

Prime implicates and prime implicants have proven relevant to a number of areas of artificial intelligence, most notably abductive reasoning and knowledge compilation. The purpose of this paper is to examine how these notions might be appropriately extended from propositional logic to the modal logic K. We begin the paper by considering a number of potential definitions of clauses and terms for K. The different definitions are evaluated with respect to a set of syntactic, semantic, and complexity-theoretic properties characteristic of the propositional definition. We then compare the definitions with respect to the properties of the notions of prime implicates and prime implicants that they induce. While there is no definition that perfectly generalizes the propositional notions, we show that there does exist one definition which satisfies many of the desirable properties of the propositional case. In the second half of the paper, we consider the computational properties of the selected definition. To this end, we provide sound and complete algorithms for generating and recognizing prime implicates, and we show the prime implicate recognition task to be PSPACE-complete. We also prove upper and lower bounds on the size and number of prime implicates. While the paper focuses on the logic K, all of our results hold equally well for multi-modal K and for concept expressions in the description logic ALC.

scholarly journals The Co-Constructed Logic Framework for Understanding Children’s Acts and Their Intentions

2021 ◽  
Vol 11 (11) ◽  
pp. 1445-1451
Author(s):  
Hongya Fan ◽  
Zeshan Ren
Keyword(s):  
Artificial Intelligence ◽  
Question Answering ◽  
Point Of View ◽  
Abductive Reasoning ◽  
Language Understanding ◽  
Reasoning Abilities ◽  
Children And Parents ◽  
Coherence Relations ◽  
Working Together ◽  
Conversational Turns

With the characteristics of the nonmonotonic logic and defeasible inference, abductive reasoning has been formalized in the field of artificial intelligence, dealing with the local pragmatics (e.g., the resolution of coreference, resolving syntactic and lexical ambiguity and interpreting metonymy and metaphor), recognizing discourse structure and even the speaker’s plan and other issues for natural language understanding. However, Hobbs’ analysis of abduction in recognizing the speaker’s plan was conducted only from the point of view of the verbal information processing that the listener does. To demonstrate the collaborative way that conversational partners working together to understand the logic of human acts and their intentions, this article analyzes the two conversations about the parents questioning their children’s intention for their acts with an abductive reasoning method. The results show that children and parents co-construct segments of discourse with coherence relations across several conversational turns, by that way they build together a simplified framework for understanding the logic of human acts and their intention. For example, when the father and his children co-constructed coherent segments of discourse with the result relation between them, they completed the particular intention understanding at the same time. This research helps in enriching the logic structure of artificial intelligence applications such as visual question answering models and enhancing their reasoning abilities.

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