At its core, a causal agent is a "thing" with the power to change the world by causing an effect [20].
Unlike standard AI which is often reactive, Agentic AI with causal understanding can anticipate the consequences of its actions and identify the true mechanisms behind data trends (e.g., recognizing that "stress" is the real cause of weight gain during exams, not the exams themselves) [25, 35]. causal agent
In scientific research, identifying the causal agent is critical for developing interventions. At its core, a causal agent is a
These frameworks, such as those developed by the UCL Center for Artificial Intelligence , integrate Large Language Models (LLMs) with causal discovery tools to generate graphs illustrating how different variables influence each other [5.4]. These frameworks, such as those developed by the
The most reliable way to identify a causal agent is through randomized controlled experiments (such as A/B tests), where one group receives a "treatment" from the agent and another does not [12]. 2. Applications in Artificial Intelligence
Researchers look for causal agents to determine if an intervention should be applied to the subject (like a vaccine) or the agent itself (like boiling contaminated water) [17].
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