Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
96 tokens/sec
Gemini 2.5 Pro Premium
44 tokens/sec
GPT-5 Medium
18 tokens/sec
GPT-5 High Premium
18 tokens/sec
GPT-4o
105 tokens/sec
DeepSeek R1 via Azure Premium
83 tokens/sec
GPT OSS 120B via Groq Premium
475 tokens/sec
Kimi K2 via Groq Premium
259 tokens/sec
2000 character limit reached

Information Acquisition and Time-Risk Preference (1809.05120v3)

Published 13 Sep 2018 in econ.TH

Abstract: An agent acquires information dynamically until her belief about a binary state reaches an upper or lower threshold. She can choose any signal process subject to a constraint on the rate of entropy reduction. Strategies are ordered by "time risk"-the dispersion of the distribution of threshold-hitting times. We construct a strategy maximizing time risk (Greedy Exploitation) and one minimizing it (Pure Accumulation). Under either strategy, beliefs follow a compensated Poisson process. In the former, beliefs jump to the threshold that is closer in Bregman divergence. In the latter, beliefs jump to the unique point with the same entropy as the current belief.

Summary

We haven't generated a summary for this paper yet.

Dice Question Streamline Icon: https://streamlinehq.com

Follow-up Questions

We haven't generated follow-up questions for this paper yet.

Don't miss out on important new AI/ML research

See which papers are being discussed right now on X, Reddit, and more:

“Emergent Mind helps me see which AI papers have caught fire online.”

Philip

Philip

Creator, AI Explained on YouTube