Christian11
Member
Yes, AI agents can learn in real-time using techniques like reinforcement learning (RL) and online learning. Real-time learning allows an agent to adapt and improve its performance based on ongoing interactions with its environment.
In reinforcement learning, an agent learns by exploring actions and receiving feedback (rewards or penalties) that guide future decisions. Real-time learning in RL involves continuously updating the agent’s knowledge as it gathers more experience. Online learning is another approach where an agent learns incrementally from data that becomes available over time, rather than being trained on a fixed dataset upfront.
For real-time learning, it’s crucial to have an efficient feedback loop, a well-optimized decision-making model, and systems in place to handle large volumes of data. These agents are particularly useful in dynamic environments like stock trading, gaming, or autonomous driving.
SOURCE: https://www.inoru.com/ai-agent-development-company
In reinforcement learning, an agent learns by exploring actions and receiving feedback (rewards or penalties) that guide future decisions. Real-time learning in RL involves continuously updating the agent’s knowledge as it gathers more experience. Online learning is another approach where an agent learns incrementally from data that becomes available over time, rather than being trained on a fixed dataset upfront.
For real-time learning, it’s crucial to have an efficient feedback loop, a well-optimized decision-making model, and systems in place to handle large volumes of data. These agents are particularly useful in dynamic environments like stock trading, gaming, or autonomous driving.
SOURCE: https://www.inoru.com/ai-agent-development-company