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🔄 Continual Learning

Enable AI to learn sequentially without forgetting previous knowledge

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Introduction to Continual Learning

🎯 What is Continual Learning?

Continual Learning (CL), also called lifelong learning, enables AI models to learn from a continuous stream of tasks while retaining previously acquired knowledge without catastrophic forgetting.

🧠
Human-Like Learning

Accumulate knowledge over time without forgetting past experiences

⚠️ The Catastrophic Forgetting Problem

When neural networks learn new tasks, they typically overwrite weights, causing dramatic performance degradation on previously learned tasks.

Example Scenario

• Train model on Task A (cats) → 95% accuracy

• Train same model on Task B (dogs) → 94% accuracy

• Test on Task A again → drops to 30% accuracy! 😱

🌟 Why Continual Learning Matters

🌍

Real-World Dynamics

Data distributions change over time in production systems

💾

Resource Efficiency

Avoid storing all historical data for retraining

⚡

Adaptive Systems

Continuously adapt to new information without downtime

🤖

Lifelong AI

Build agents that learn throughout their operational lifetime

📊 CL Scenarios

Task-Incremental Learning

Learn sequence of distinct tasks (task ID known at inference)

Class-Incremental Learning

New classes added over time (task ID unknown at inference)

Domain-Incremental Learning

Same task, different domains (e.g., photos → sketches)

🎯 Key Objectives

Backward Transfer

Retention

Maintain performance on old tasks after learning new ones

Forward Transfer

Generalization

Leverage past knowledge to learn new tasks faster

Memory Efficiency

Scalability

Bound memory and computational requirements as tasks grow

📈 Evaluation Metrics

Average Accuracy

Mean performance across all tasks after learning sequence

A_avg = (1/T) Σ a_t

Forgetting Measure

Average performance drop on previous tasks

F = (1/T) Σ (a_max - a_final)

Forward Transfer

Performance on task T influenced by tasks 1...T-1

Backward Transfer

Change in performance on task t after learning task T