AIMC Topic: Problem Solving

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Characterization of Industry 4.0 Lean Management Problem-Solving Behavioral Patterns Using EEG Sensors and Deep Learning.

Sensors (Basel, Switzerland)
Industry 4.0 leaders solve problems all of the time. Successful problem-solving behavioral pattern choice determines organizational and personal success, therefore a proper understanding of the problem-solving-related neurological dynamics is sure to...

Combining Hopfield neural networks, with applications to grid-based mathematics puzzles.

Neural networks : the official journal of the International Neural Network Society
Hopfield neural networks are useful for solving certain constrained set-selection problems. We establish that the vector fields associated with general networks of this type can be combined to produce a new network that solves the corresponding combi...

Evolutionary Spiking Neural Networks for Solving Supervised Classification Problems.

Computational intelligence and neuroscience
This paper presents a grammatical evolution (GE)-based methodology to automatically design third generation artificial neural networks (ANNs), also known as spiking neural networks (SNNs), for solving supervised classification problems. The proposal ...

Direct Feature Evaluation in Black-Box Optimization Using Problem Transformations.

Evolutionary computation
Exploratory Landscape Analysis provides sample-based methods to calculate features of black-box optimization problems in a quantitative and measurable way. Many problem features have been proposed in the literature in an attempt to provide insights i...

Individual differences in rate of acquiring stable neural representations of tasks in fMRI.

PloS one
Task-related functional magnetic resonance imaging (fMRI) is a widely-used tool for studying the neural processing correlates of human behavior in both healthy and clinical populations. There is growing interest in mapping individual differences in f...

Intelligent machines, care work and the nature of practical reasoning.

Nursing ethics
BACKGROUND: The debate over the ethical implications of care robots has raised a range of concerns, including the possibility that such technologies could disrupt caregiving as a core human moral activity. At the same time, academics in information e...

A Novel Teaching-Learning-Based Optimization with Error Correction and Cauchy Distribution for Path Planning of Unmanned Air Vehicle.

Computational intelligence and neuroscience
Teaching-learning-based optimization (TLBO) algorithm is a novel heuristic method which simulates the teaching-learning phenomenon of a classroom. However, in the later period of evolution of the TLBO algorithm, the lower exploitation ability and the...

Learning to activate logic rules for textual reasoning.

Neural networks : the official journal of the International Neural Network Society
Most current textual reasoning models cannotlearn human-like reasoning process, and thus lack interpretability and logical accuracy. To help address this issue, we propose a novel reasoning model which learns to activate logic rules explicitly via de...

Visual mental imagery: A view from artificial intelligence.

Cortex; a journal devoted to the study of the nervous system and behavior
This article investigates whether, and how, an artificial intelligence (AI) system can be said to use visual, imagery-based representations in a way that is analogous to the use of visual mental imagery by people. In particular, this article aims to ...