Replay memory is a machine learning technique that stores and reuses past experiences to enhance an agent's decision-making. Common in reinforcement learning, it helps agents learn from diverse situations, improving performance in applications like game AI, robotics, and autonomous vehicles.
Hyperparameter tuning optimises AI model performance by finding the best parameter settings. It improves accuracy, saves resources, and is crucial for AI development. It also prevents overfitting, where a model learns to perform exceptionally well on the training data but fails with new unseen data
Multi-agent systems (MAS) embody an innovative approach in artificial intelligence, where multiple autonomous agents collaborate and interact to address complex problems, showcasing their adaptability and efficiency across a wide range of applications, such as robotics, smart grids, and e-commerce.
As we continue to develop and integrate AI into various aspects of our lives, it's crucial to recognize the distinctions between the two primary forms of intelligence: Artificial General Intelligence (AGI) and Narrow AI.
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