https://www.youtube.com/watch?v=EDb37y_M
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https://www.youtube.com/@IBMTechnology
https://www.ibm.com/think/topics/ai-agent-types
Learning agents are highly flexible and capable of handling complex, ever-changing environments. They are useful in applications such as autonomous driving, robotics and virtual assistants that assist human agents in customer support.
The ability to learn from interactions makes learning agents valuable for applications in fields such as persistent chatbots and social media, where natural language processing (NLP) analyzes user behavior to predict and optimize content recommendations.
Multi agent:
As AI systems become more intricate, the need for hierarchical agents arises. These agents are designed to break down complex problems into smaller, manageable subtasks, making it easier to handle complex problems in real-world scenarios. Higher-level agents focus on overarching goals, while lower-level agents handle more specific tasks.
An AI orchestration that integrates the different types of AI agents can make for a highly intelligent and adaptive multi-agent system capable of managing complex tasks across multiple domains.