DRL Agents
Reinforcement learning (RL) is a type of machine learning that is inspired by the way animals and humans learn from their environment through trial and error. In RL, an agent interacts with an environment, making observations and taking actions in response to those observations. The environment provides feedback in the form of rewards or penalties, which the agent uses to update its behavior. By repeating this process over time, the agent learns to make decisions that lead to higher rewards and achieve its objectives, even in complex and dynamic environments.
DRL AGENTS : ARTIFICIAL INTELLIGENCE FOR YOUR INNOVATION
At DELFOX, we're driving AI forward by harnessing the potential of DRL (Deep Reinforcement Learning) Agents. Discover how these deep reinforcement learning systems can catalyze your innovation projects.
WHAT IS A DRL AGENT?
DRL Agents embody a new era of autonomous, adaptive learning. A DRL Agent is software capable of learning and making decisions autonomously by interacting with a complex environment, it could represent a drone, a fighter jet or a car, depending of the use case. Basically, it combines the power of Deep Learning with the principles of Reinforcement Learning, enabling it to optimize its actions by maximizing the rewards it receives.
HOW DOES A DRL AGENT WORK?
A DRL Agent works by following an iterative decision-making process. It observes the state of its environment, selects an action, receives a reward or punishment for that action, and adjusts its strategies to maximize future rewards. This continuous feedback loop enables the agent to adapt to changes and learn autonomously.
HOW IS A DRL AGENT TRAINED?
Training a DRL Agent is a crucial step. It begins with the creation of a simulated environment in which the agent can evolve. Our teams of experts, in close collaboration with your teams, define the training parameters and objectives. The agent learns by interacting with this simulated environment, receiving positive or negative rewards depending on its actions. It continually adjusts its strategies to maximize gains, thus perfecting its behavior.
THE ADVANTAGES OF THE trained DRL AGENT:
- Adaptability: They excel in dynamic, changing environments, adapting autonomously.
- Performance: DRL Agents have demonstrated their ability to excel in a variety of fields, from robotics to finance.
- Uncertainty Management: They excel in decision-making under uncertainty, providing a competitive edge.
- Action hierarchy: DRL Agents can learn hierarchies of actions to solve complex problems.
- Versatile applications: DRL Agents can be used in a wide range of industries, including aerospace and defense.
HOW TO EXPORT THE DRL AGENT?
The final export of your DRL Agent is the key phase. DELFOX supports you in this transition by ensuring that your agent can make autonomous decisions safely in the real world. Our expertise guarantees integration via a software brick adapted to your application or in universal format (ONNX), unleashing the potential of artificial intelligence to drive your innovation.