Paradigm Swarm: Structural Prevention of Catastrophic Forgetting through Semantic Weight Isolation

Key Points

• This research aims to address catastrophic forgetting in continual learning architectures through a novel structure that isolates knowledge into experts.
• Developed the Paradigm Swarm architecture with frozen weights across expert paradigms.
• Conducted 28 experimental configurations, including synthetic datasets and CIFAR-100.
• Executed 45 reproducible experiments using NumPy for validation.
• Paradigm Swarm matches Oracle's accuracy within 0.002 points.
• SGD exhibited a maximum forgetting of 57 percentage points in contrast to Paradigm Swarm.
• Demonstrated properties such as zero forgetting by design and enhanced gap detection capabilities.