Multi-Objective Reinforcement Learning (MORL) is an emerging field that extends the conventional reinforcement learning paradigm by enabling agents to optimise multiple conflicting objectives ...

Deep reinforcement learning is having a superstar moment. Powering smarter robots. Simulating human neural networks. Trouncing physicians at medical diagnoses and crushing humanity’s best gamers at Go ...

From its earliest days, artificial intelligence (AI) has captivated and enticed the business world with its potential ability to learn not only to imitate humans but to supersede our capabilities. As ...

Deep Reinforcement Learning (DRL) is a subfield of machine learning that combines neural networks with reinforcement learning techniques to make decisions in complex environments. It has been applied ...

At the core of reinforcement learning is the concept that the optimal behavior or action is reinforced by a positive reward. Similar to toddlers learning how to walk who adjust actions based on the ...

Social learning theory, developed by psychologist Albert Bandura, uses theories of classical and operant conditioning. But in this theory, the environment plays a large part in learning. We model the ...