Category: Artificial Intelligence

Graph Attention Networks

Graph Attention Networks, or GATs, are a type of neural network designed to work with data structured as graphs. Unlike traditional neural networks that process fixed-size data like images or text, GATs can handle nodes and their connections directly. They use an attention mechanism to decide which neighbouring nodes are most important when making predictions…

Actor-Critic Methods

Actor-Critic Methods are a group of algorithms used in reinforcement learning where two components work together to help an agent learn. The actor decides which actions to take, while the critic evaluates how good those actions are based on the current situation. This collaboration allows the agent to improve its decision-making over time by using…

Proximal Policy Optimization (PPO)

Proximal Policy Optimization (PPO) is a type of algorithm used in reinforcement learning to train agents to make good decisions. PPO improves how agents learn by making small, safe updates to their behaviour, which helps prevent them from making drastic changes that could reduce their performance. It is popular because it is relatively easy to…

Monte Carlo Tree Search

Monte Carlo Tree Search (MCTS) is a computer algorithm used to make decisions, especially in games or situations where there are many possible moves and outcomes. It works by simulating many random possible futures from the current situation, then using the results to decide which move gives the best chance of success. MCTS gradually builds…

Temporal Difference Learning

Temporal Difference Learning is a method used in machine learning where an agent learns how to make decisions by gradually improving its predictions based on feedback from its environment. It combines ideas from dynamic programming and Monte Carlo methods, allowing learning from incomplete sequences of events. This approach helps the agent adjust its understanding over…

Explainable AI (XAI)

Explainable AI (XAI) refers to methods and techniques that make the decisions and actions of artificial intelligence systems understandable to humans. Unlike traditional AI models, which often act as black boxes, XAI aims to provide clear reasons for how and why an AI system arrived at a particular result. This transparency helps users trust and…

Causal Inference

Causal inference is the process of figuring out whether one thing actually causes another, rather than just being linked or happening together. It helps researchers and decision-makers understand if a change in one factor will lead to a change in another. Unlike simple observation, causal inference tries to rule out other explanations or coincidences, aiming…