AIMC Topic: Problem Solving

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Participatory approach to the development of a knowledge base for problem-solving in diabetes self-management.

International journal of medical informatics
OBJECTIVE: To develop an expandable knowledge base of reusable knowledge related to self-management of diabetes that can be used as a foundation for patient-centric decision support tools.

A Hybrid alldifferent-Tabu Search Algorithm for Solving Sudoku Puzzles.

Computational intelligence and neuroscience
The Sudoku problem is a well-known logic-based puzzle of combinatorial number-placement. It consists in filling a n(2) × n(2) grid, composed of n columns, n rows, and n subgrids, each one containing distinct integers from 1 to n(2). Such a puzzle bel...

A rational model of function learning.

Psychonomic bulletin & review
Theories of how people learn relationships between continuous variables have tended to focus on two possibilities: one, that people are estimating explicit functions, or two that they are performing associative learning supported by similarity. We pr...

Error bounds of adaptive dynamic programming algorithms for solving undiscounted optimal control problems.

IEEE transactions on neural networks and learning systems
In this paper, we establish error bounds of adaptive dynamic programming algorithms for solving undiscounted infinite-horizon optimal control problems of discrete-time deterministic nonlinear systems. We consider approximation errors in the update eq...

Solving nonlinear equality constrained multiobjective optimization problems using neural networks.

IEEE transactions on neural networks and learning systems
This paper develops a neural network architecture and a new processing method for solving in real time, the nonlinear equality constrained multiobjective optimization problem (NECMOP), where several nonlinear objective functions must be optimized in ...

Generative AI without guardrails can harm learning: Evidence from high school mathematics.

Proceedings of the National Academy of Sciences of the United States of America
Generative AI is poised to revolutionize how humans work, and has already demonstrated promise in significantly improving human productivity. A key question is how generative AI affects learning-namely, how humans acquire new skills as they perform t...

Improving generalization of neural Vehicle Routing Problem solvers through the lens of model architecture.

Neural networks : the official journal of the International Neural Network Society
Neural models produce promising results when solving Vehicle Routing Problems (VRPs), but may often fall short in generalization. Recent attempts to enhance model generalization often incur unnecessarily large training cost or cannot be directly appl...

A Layered Learning Approach to Scaling in Learning Classifier Systems for Boolean Problems.

Evolutionary computation
Evolutionary Computation (EC) often throws away learned knowledge as it is reset for each new problem addressed. Conversely, humans can learn from small-scale problems, retain this knowledge (plus functionality), and then successfully reuse them in l...