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Daniel Rosel
2026-04-09 22:03:53 +02:00
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paper/src/summary.tex
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@@ -21,7 +21,7 @@
\vspace{0.75em} \vspace{0.75em}
Large language model (LLM) agents are spreading in e-commerce; one consequence is intermediaries that can separate information gathering from transaction execution. Large language model (LLM) agents are spreading in e-commerce, one consequence is intermediaries that can separate information gathering from transaction execution.
This thesis studies dynamic pricing when agents reconnoitre in isolated sessions and thereby weaken the \emph{Cost of Information} (COI), the premium platforms typically extract once demand signals are expressed. This thesis studies dynamic pricing when agents reconnoitre in isolated sessions and thereby weaken the \emph{Cost of Information} (COI), the premium platforms typically extract once demand signals are expressed.
The key technical risk is not ``agents buying things'' per se, but agents shaping the behavioral and demand signals that downstream pricing systems consume and depend on \parencite{xia_evaluation-driven_2025}. The key technical risk is not ``agents buying things'' per se, but agents shaping the behavioral and demand signals that downstream pricing systems consume and depend on \parencite{xia_evaluation-driven_2025}.
Dynamic pricing assumes demand proxies are behaviorally meaningful, while bot detection aims at security and access control. Dynamic pricing assumes demand proxies are behaviorally meaningful, while bot detection aims at security and access control.