Agent Loops: Perceive-Reason-Act — Free AI Agents Tutorial
Learn Agent Loops: Perceive-Reason-Act in AI Agents with a free, beginner-friendly tutorial, examples and practice for Indian students on Syllab.in.
TL;DR: Learn Agent Loops: Perceive-Reason-Act in AI Agents with a free, beginner-friendly tutorial, examples and practice for Indian students on Syllab.in.
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Agent Loops: Perceive-Reason-Act in AI Agents
The agent loop is the core execution cycle: Perceive (read sensors) → Reason (process observations, decide) → Act (execute actions) → Repeat. This loop runs continuously, driving agent behavior.
Well-designed loops are efficient (not too slow), responsive (detect changes), and safe (include stopping conditions). A tutoring agent might loop every 5 seconds, checking for student input. An autonomous vehicle might loop 100+ times per second.
Loop conditions matter: What triggers the loop? When does it stop? An adaptive learning agent might loop continuously throughout a study session. A homework grader agent might loop once per submission.
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