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Equation 2 · Comparing the Main Approaches to AI Agent Architecture

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o≤to_{\le t}

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o≤to_{\le t}

Symbol o_ ≤ t

the observation history.

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subscript

subscript

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where o≤to_{\le t} is the observation history, hth_t is whatever state the system has chosen to retain, and g is the task goal. Nothing here is specific to language models; it is the generic shape of a controller. What actually distinguishes the four patterns below is not this equation but what each one does with hth_t : whether it is one growing transcript, a plan object computed once and then held fixed, a set of disjoint per-worker histories that never touch each other directly, or a position in an explicit graph whose edges may or may not be permitted to fire. The rest of this article works through each shape in turn, using the tradeoffs their own architects have written down, not a synthetic…
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where o≤to_{\le t} is the observation history, hth_t is whatever state the system has chosen to retain, and g is the task goal. Nothing here is specific to language models; it is the generic shape of a controller. What actually distinguishes the four patterns below is not this equation but what each one does with hth_t : whether it is one growing transcript, a plan object computed once and then held fixed, a set of disjoint per-worker histories that never touch each other directly, or a position in an explicit graph whose edges may or may not be permitted to fire. The rest of this article works through each shape in turn, using the tradeoffs their own architects have written down, not a synthetic score.

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