Inverse Reinforcement Learning (IRL) is a machine learning technique where an algorithm learns what motivates an expert by observing their behaviour, instead of being told directly what to do. Rather than specifying a reward function upfront, IRL tries to infer the underlying goals or rewards that drive the expert’s actions. This approach is useful for…
Category: Autonomous Systems
Hierarchical Reinforcement Learning
Hierarchical Reinforcement Learning (HRL) is an approach in artificial intelligence where complex tasks are broken down into smaller, simpler sub-tasks. Each sub-task can be solved with its own strategy, making it easier to learn and manage large problems. By organising tasks in a hierarchy, systems can reuse solutions to sub-tasks and solve new problems more…
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…
Command and Control (C2)
Command and Control (C2) refers to the process by which leaders direct and manage resources, personnel, and operations to achieve specific goals. It involves making decisions, issuing orders, and ensuring that those orders are followed effectively. C2 systems help coordinate actions, share information, and maintain oversight in complex environments, such as military operations, emergency management,…