An AI-integrated infrastructure framework embeds real-time diagnostics, reinforcement learning, and multi-agent coordination into distributed ...
Multi-agent reinforcement learning (MARL) algorithms play an essential role in solving complex decision-making tasks by learning from the interaction data between computerized agents and (simulated) ...
ADELPHI, Md. — Army scientists developed an innovative method for evaluating the learned behavior of black-box Multi-Agent Reinforcement Learning, known as MARL, agents performing a pursuit-evasion ...
ADELPHI, Md. -- Army researchers developed a reinforcement learning approach that will allow swarms of unmanned aerial and ground vehicles to optimally accomplish various missions while minimizing ...
The overall relationship between the attacker and the ego system. The black solid arrows indicate the direction of data flow, the red solid ones indicate the direction of gradient flow and the red ...
Kimi K2.5 introduces a multi-agent orchestration with up to 100 workers, helping teams cut complex task time and boost ...
Reinforcement learning is a subfield of machine learning concerned with how an intelligent agent can learn through trial and error to make optimal decisions in its ...
In June 2021, scientists at the AI lab DeepMind made a controversial claim. The researchers suggested that we could reach artificial general intelligence (AGI) using one single approach: reinforcement ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results