AIMC Topic: Symbolism

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PROSE: Predicting Multiple Operators and Symbolic Expressions using multimodal transformers.

Neural networks : the official journal of the International Neural Network Society Sep 20, 2024
Approximating nonlinear differential equations using a neural network provides a robust and efficient tool for various scientific computing tasks, including real-time predictions, inverse problems, optimal controls, and surrogate modeling. Previous w...
Humans Neural Networks, Computer Nonlinear Dynamics Symbolism Algorithms Language
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Artificial lives, analogies and symbolic thought: an anthropological insight on robots and AI.

Studies in history and philosophy of science May 2, 2023
The aim of this article is to explore the conception of artificial life forms and the interactions we have with them by paying a particular attention to the analogies that characterize them and the mental processes they give rise to. The article adop...
Anthropology, Cultural Humans Anthropology Robotics Symbolism Mental Processes
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Training neural networks to encode symbols enables combinatorial generalization.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences Dec 16, 2019
Combinatorial generalization-the ability to understand and produce novel combinations of already familiar elements-is considered to be a core capacity of the human mind and a major challenge to neural network models. A significant body of research su...
Humans Learning Symbolism Neural Networks, Computer Computer Simulation
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Training Feedforward Neural Networks Using Symbiotic Organisms Search Algorithm.

Computational intelligence and neuroscience Dec 25, 2016
Symbiotic organisms search (SOS) is a new robust and powerful metaheuristic algorithm, which stimulates the symbiotic interaction strategies adopted by organisms to survive and propagate in the ecosystem. In the supervised learning area, it is a chal...
Analysis of Variance Computer Simulation Humans Neural Networks, Computer Symbolism Learning Algorithms Feedback Data Mining
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Robust sensorimotor representation to physical interaction changes in humanoid motion learning.

IEEE transactions on neural networks and learning systems Jul 10, 2014
This paper proposes a learning from demonstration system based on a motion feature, called phase transfer sequence. The system aims to synthesize the knowledge on humanoid whole body motions learned during teacher-supported interactions, and apply th...
Motor Activity Symbolism Transfer, Psychology Humans Functional Laterality Computer Simulation Knowledge Motion Robotics Learning Walking Time Factors
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A review of computational models of basic rule learning: The neural-symbolic debate and beyond.

Psychonomic bulletin & review Aug 1, 2019
We present a critical review of computational models of generalization of simple grammar-like rules, such as ABA and ABB. In particular, we focus on models attempting to account for the empirical results of Marcus et al. (Science, 283(5398), 77-80 19...
Infant Models, Psychological Computer Simulation Learning Language Development Symbolism Generalization, Psychological Humans Neural Networks, Computer
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[Artificial intelligence for future MD].

Giornale italiano di nefrologia : organo ufficiale della Societa italiana di nefrologia Dec 1, 2018
Health care workers need artificial intelligence. Artificial intelligence is a set of studies and techniques that tend to the realization of machines, which solve complex problems automatically, simulating or emulating human intelligence activities. ...
Speech Recognition Software Symbolism Education, Medical Humans Medical Informatics Forecasting Intelligence Computers Learning Robotics Neural Networks, Computer Artificial Intelligence Machine Learning Algorithms
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