AIMC Topic: Problem Solving

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When is Psychology Research Useful in Artificial Intelligence? A Case for Reducing Computational Complexity in Problem Solving.

Topics in cognitive science Aug 31, 2021
A problem is a situation in which an agent seeks to attain a given goal without knowing how to achieve it. Human problem solving is typically studied as a search in a problem space composed of states (information about the environment) and operators ...
Humans Artificial Intelligence Reward Problem Solving Algorithms Heuristics
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Human-in-the-Loop Low-Shot Learning.

IEEE transactions on neural networks and learning systems Jul 6, 2021
We consider a human-in-the-loop scenario in the context of low-shot learning. Our approach was inspired by the fact that the viability of samples in novel categories cannot be sufficiently reflected by those limited observations. Some heterogeneous s...
Humans Algorithms Learning Neural Networks, Computer Machine Learning Uncertainty Problem Solving Reinforcement, Psychology Feedback
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A Neural Network Based on the Metric Projector for Solving SOCCVI Problem.

IEEE transactions on neural networks and learning systems Jul 6, 2021
We propose an efficient neural network for solving the second-order cone constrained variational inequality (SOCCVI). The network is constructed using the Karush-Kuhn-Tucker (KKT) conditions of the variational inequality (VI), which is used to recast...
Neural Networks, Computer Nonlinear Dynamics Problem Solving Algorithms Computer Simulation
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BARD: A Structured Technique for Group Elicitation of Bayesian Networks to Support Analytic Reasoning.

Risk analysis : an official publication of the Society for Risk Analysis Jun 19, 2021
In many complex, real-world situations, problem solving and decision making require effective reasoning about causation and uncertainty. However, human reasoning in these cases is prone to confusion and error. Bayesian networks (BNs) are an artificia...
Uncertainty Problem Solving Humans Artificial Intelligence Software Bayes Theorem
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HiAM: A Hierarchical Attention based Model for knowledge graph multi-hop reasoning.

Neural networks : the official journal of the International Neural Network Society Jun 9, 2021
Learning to reason in large-scale knowledge graphs has attracted much attention from research communities recently. This paper targets a practical task of multi-hop reasoning in knowledge graphs, which can be applied in various downstream tasks such ...
Neural Networks, Computer Semantics Pattern Recognition, Automated Knowledge Problem Solving
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Reimagining robotic walkers for real-world outdoor play environments with insights from legged robots: a scoping review.

Disability and rehabilitation. Assistive technology Jun 4, 2021
PURPOSE: For children with mobility impairments, without cognitive delays, who want to participate in outdoor activities, existing assistive technology (AT) to support their needs is limited. In this review, we investigate the control and design of a...
Walkers Self-Help Devices Child Persons with Disabilities Robotics Problem Solving Humans
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A New Initialization Approach in Particle Swarm Optimization for Global Optimization Problems.

Computational intelligence and neuroscience May 17, 2021
Particle swarm optimization (PSO) algorithm is a population-based intelligent stochastic search technique used to search for food with the intrinsic manner of bee swarming. PSO is widely used to solve the diverse problems of optimization. Initializat...
Animals Bees Neural Networks, Computer Algorithms Problem Solving Learning
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Vision-Language-Knowledge Co-Embedding for Visual Commonsense Reasoning.

Sensors (Basel, Switzerland) Apr 21, 2021
Visual commonsense reasoning is an intelligent task performed to decide the most appropriate answer to a question while providing the rationale or reason for the answer when an image, a natural language question, and candidate responses are given. Fo...
Natural Language Processing Problem Solving Neural Networks, Computer Language
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Solving infinite-horizon optimalcontrol problems of the time-delayedsystems by a feed forward neural network model.

Network (Bristol, England) Apr 19, 2021
A numerical method using neural network for solving infinite-horizon time-delayed optimal control problems is studied. The problem is first transformed, using a Páde approximation, to one without a time-delayed argument. By a suitable change of varia...
Time Factors Problem Solving Research Design Neural Networks, Computer
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Review of Temporal Reasoning in the Clinical Domain for Timeline Extraction: Where we are and where we need to be.

Journal of biomedical informatics Apr 14, 2021
Understanding a patient's medical history, such as how long symptoms last or when a procedure was performed, is vital to diagnosing problems and providing good care. Frequently, important information regarding a patient's medical timeline is buried i...
Problem Solving Time Electronic Health Records Natural Language Processing Humans
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