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The Algorithmic Advantage: How Reinforcement Learning Generates Rich Communication

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Listed:
  • Emilio Calvano
  • Clemens Possnig
  • Juha Tolvanen

Abstract

We analyze strategic communication when advice is generated by a reinforcement-learning algorithm rather than by a fully rational sender. Building on the cheap-talk framework of Crawford and Sobel (1982), an advisor adapts its messages based on payoff feedback, while a decision maker best-responds. We provide a theoretical analysis of the long-run communication outcomes induced by such reward-driven adaptation. With aligned preferences, we establish that learning robustly leads to informative communication even from uninformative initial policies. With misaligned preferences, no stable outcome exists; instead, learning generates cycles that sustain highly informative communication and payoffs exceeding those of any static equilibrium.

Suggested Citation

  • Emilio Calvano & Clemens Possnig & Juha Tolvanen, 2026. "The Algorithmic Advantage: How Reinforcement Learning Generates Rich Communication," Papers 2602.12035, arXiv.org.
    • Handle: RePEc:arx:papers:2602.12035
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    File URL: http://arxiv.org/pdf/2602.12035
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