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Problem Solving

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A new ML-based approach to enhance student engagement in online environment.

PloS one
The educational research is increasingly emphasizing the potential of student engagement and its impact on performance, retention and persistence. This construct has emerged as an important paradigm in the higher education field for many decades. How...

HiAM: A Hierarchical Attention based Model for knowledge graph multi-hop reasoning.

Neural networks : the official journal of the International Neural Network Society
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 ...

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

Topics in cognitive science
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 ...

Is Artificial Intelligence Customer Service Satisfactory? Insights Based on Microblog Data and User Interviews.

Cyberpsychology, behavior and social networking
A growing number of sectors are delivering customer services powered by artificial intelligence (AI) instead of humans, with evidence indicating labor cost reduction and efficiency improvement. However, it would be worthwhile to examine the extent to...

Real-Time Detection of Cook Assistant Overalls Based on Embedded Reasoning.

Sensors (Basel, Switzerland)
Currently, the target detection based on convolutional neural network plays an important role in image recognition, speech recognition and other fields. However, the current network model features a complex structure, a huge number of parameters and ...

TextRank Keyword Extraction Algorithm Using Word Vector Clustering Based on Rough Data-Deduction.

Computational intelligence and neuroscience
When TextRank algorithm based on graph model constructs graph associative edges, the co-occurrence window rules only consider the relationships between local terms. Using the information in the document itself is limited. In order to solve the above ...

Learning to Reason on Tree Structures for Knowledge-Based Visual Question Answering.

Sensors (Basel, Switzerland)
Collaborative reasoning for knowledge-based visual question answering is challenging but vital and efficient in understanding the features of the images and questions. While previous methods jointly fuse all kinds of features by attention mechanism o...

Understanding the Computational Demands Underlying Visual Reasoning.

Neural computation
Visual understanding requires comprehending complex visual relations between objects within a scene. Here, we seek to characterize the computational demands for abstract visual reasoning. We do this by systematically assessing the ability of modern d...

Evolving Multimodal Robot Behavior via Many Stepping Stones with the Combinatorial Multiobjective Evolutionary Algorithm.

Evolutionary computation
An important challenge in reinforcement learning is to solve multimodal problems, where agents have to act in qualitatively different ways depending on the circumstances. Because multimodal problems are often too difficult to solve directly, it is of...

Variable Binding for Sparse Distributed Representations: Theory and Applications.

IEEE transactions on neural networks and learning systems
Variable binding is a cornerstone of symbolic reasoning and cognition. But how binding can be implemented in connectionist models has puzzled neuroscientists, cognitive psychologists, and neural network researchers for many decades. One type of conne...