How to mitigate catastrophic forgetting for an intelligent agent using ...

It seems to me a case of catastrophic forgetting (I could be wrong) and I managed to mitigate it by increasing the memory, retaining the results ...

Overcoming catastrophic forgetting in neural networks - PNAS

It does so by selectively decreasing the plasticity of weights and thus has certain parallels with neurobiological models of synaptic consolidation (15, 16). We ...

Catastrophic Forgetting: The Essential Guide | Nightfall AI Security 101

The root of catastrophic forgetting lies in the way neural networks update their weights. When a network learns a new task, it modifies its weights to reduce ...

Mitigating Catastrophic Forgetting in Large-Scale Models with ...

One of the effective methods for combating catastrophic forgetting in continuous learning models is the use of replay-based methods. These ...

Techniques for Tackling Catastrophic Forgetting in AI Models

Preventing catastrophic forgetting is done using three approaches: regularization, memory-based techniques, and architecture-based methods.

Catastrophic Forgetting: Understanding AI Memory Loss - ProjectPro

Use strategies such as continual learning frameworks, meta-learning approaches, and ensemble methods to manage the trade-off between learning ...

Overcoming 'Catastrophic Forgetting': A Leap in AI Continuous ...

Artificial neural networks remember information better when presented with a variety of tasks, rather than tasks sharing similar attributes. The ...

Addressing 'Catastrophic forgetting' in Generative AI - LinkedIn

Ensemble Learning: Combining multiple models trained on different tasks can leverage their complementary strengths and mitigate forgetting for ...

A bio-inspired technique to mitigate catastrophic forgetting in ...

The consolidation mechanism introduced in the recent paper could help to mitigate catastrophic forgetting in binarized neural networks, enabling ...

Overcoming catastrophic forgetting in neural networks - arXiv

Critically, therefore, intelligent agents must demonstrate a ... order to mitigate catastrophic forgetting ... While augmenting the DQN agent with ...

Catastrophic Forgetting in Neural Networks - DEV

One of the main causes of catastrophic forgetting is task interference and overlap, where patterns learned for one task can unintentionally ...

Alleviating catastrophic forgetting using context-dependent gating ...

In this study, we have shown that XdG, used in conjunction with previous methods to stabilize synapses, can alleviate catastrophic forgetting in ...

Complementary Learning for Overcoming Catastrophic Forgetting ...

It is in contrast with continual learning ability of humans over their lifetime. To mitigate catastrophic forgetting, one of the main ap- proaches is to replay ...

Tackling Catastrophic Forgetting in Neural Networks - Restack

Memory-based techniques involve replaying learned instances to mitigate forgetting. Two notable methods are: ... These strategies collectively ...

Overcoming Catastrophic Forgetting: A Simple Guide to Elastic ...

In the field of artificial intelligence, deep learning models, especially neural networks, have shown great success in a wide range of ...

Understanding and Mitigating Catastrophic Forgetting in Machine ...

1. · 3. Inhibited Autonomous Learning: · 2. Regularization Techniques: · 3. Modular Architectures: Designing neural networks with modular ...

Catastrophic forgetting in machine learning - Scanbot SDK

One way to minimize catastrophic forgetting is to ensure that when weights fine-tuned for task 1 are trained for task 2, they stay within a ...

Consistency is the key to further mitigating catastrophic forgetting in ...

Rehearsal-based methods which explicitly store previous task samples in the buffer and interleave them with the current task samples have proven ...

Understanding Catastrophic Forgetting in Large Language Models

Catastrophic forgetting occurs due to the nature of the optimization process during training. When a model trains to minimize the current task's ...

Avoiding Catastrophic Forgetting - ScienceDirect.com

A recent article presents an algorithm that spares learning at synapses important for previously learned function, reducing catastrophic forgetting. Section ...