Effective task allocation has become a critical challenge for multi-robot systems operating in dynamic environments like search and rescue. Traditional methods, often based on static data and ...

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 ...

Reinforcement learning is a subset of machine learning. It enables an agent to learn through the consequences of actions in a specific environment. It can be used to teach a robot new tricks, for ...

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

This article is published by AllBusiness.com, a partner of TIME. What is "Reinforcement Learning"? Reinforcement Learning (RL) is a type of machine learning where a model learns to make decisions by ...

Ambuj Tewari receives funding from NSF and NIH. Understanding intelligence and creating intelligent machines are grand scientific challenges of our times. The ability to learn from experience is a ...

Whether you like theoretical study or want to get your hands dirty, plenty of reinforcement learning resources are out there. When I was in graduate school in the 1990s, one of my favorite classes was ...