This overview provides you with a basic understanding of how many experts approach new AI agents.
I am an MIT Senior Fellow & Lecturer, 5x-founder & VC investing in AISUQIAN, CHINA - JUNE 10: In this photo illustration, the logo of AI Agent is displayed on asmartphone screen on June 10, 2025 in Suqian, Jiangsu Province of China. The era of agentic AI is upon us. We have new enterprise systems utilizing this framework where increasingly, specialized models are doing different parts of a complex task.
The next step up is a model-based reflex agent. This agent type can maintain some sort of internal model of how the world works, and updates using percept history, also combining current percept data to decide actions. In general, it’s suitable for dynamic or “partially known” environments where there may be wildcards, but also sorted info.
The utility-based agent, a step up, has the additional capability of contrasting different criteria in a rule based system. In other words, it can make rational tradeoffs between conflicting goals, and choose actions that maximize expected utility. This type of agent is well suited to complex, uncertain environments, because it has more sophisticated decision-making than goal-based agents.
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