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Temporal Ontogeny of Epileptogenesis in a Model of Adult-onset, Spontaneous Seizures
Title
Temporal Ontogeny of Epileptogenesis in a Model of Adult-onset, Spontaneous Seizures.
Creator
Melanie Gil, Rachel St. Clair, Ceylan Isgor
Date Issued
2017
PURL
http://purl.flvc.org/fau/fd/FAU_SR00000010
Subject Headings
College students --Research --United States.
Format
Document (PDF)
PRESERVING KNOWLEDGE IN SIMULATED BEHAVIORAL ACTION LOOPS
Title
PRESERVING KNOWLEDGE IN SIMULATED BEHAVIORAL ACTION LOOPS.
Creator
St.Clair, Rachel, Barenholtz, Elan, Hahn, William, Florida Atlantic University, Center for Complex Systems and Brain Sciences, Charles E. Schmidt College of Science
Abstract/Description
One basic goal of artificial learning systems is the ability to continually learn throughout that system’s lifetime. Transitioning between tasks and re-deploying prior knowledge is thus a desired feature of artificial learning. However, in the deep-learning approaches, the problem of catastrophic forgetting of prior knowledge persists. As a field, we want to solve the catastrophic forgetting problem without requiring exponential computations or time, while demonstrating real-world relevance....
Show moreOne basic goal of artificial learning systems is the ability to continually learn throughout that system’s lifetime. Transitioning between tasks and re-deploying prior knowledge is thus a desired feature of artificial learning. However, in the deep-learning approaches, the problem of catastrophic forgetting of prior knowledge persists. As a field, we want to solve the catastrophic forgetting problem without requiring exponential computations or time, while demonstrating real-world relevance. This work proposes a novel model which uses an evolutionary algorithm similar to a meta-learning objective, that is fitted with a resource constraint metrics. Four reinforcement learning environments are considered with the shared concept of depth although the collection of environments is multi-modal. This system shows preservation of some knowledge in sequential task learning and protection of catastrophic forgetting in deep neural networks.
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Date Issued
2022
PURL
http://purl.flvc.org/fau/fd/FA00013896
Subject Headings
Artificial intelligence, Deep learning (Machine learning), Reinforcement learning, Neural networks (Computer science)
Format
Document (PDF)