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The fact that redundant information does not update a rational belief implies that rational beliefs are updated using Bayes rule. In the framework of Hild (1998a), this is true under mild conditions for discrete, continuous, and arbitrary…

We consider an information update system where an information receiver requests updates from an information provider in order to minimize its age of information. The updates are generated at the information provider (transmitter) as a…

Information Theory · Computer Science 2020-04-28 Melih Bastopcu , Sennur Ulukus

We study the stability of orbits in large Boolean networks with given complex topology. We impose no restrictions on the form of the update rules, which may be correlated with local topological properties of the network. While recent past…

Physics and Society · Physics 2014-09-05 Shane Squires , Andrew Pomerance , Michelle Girvan , Edward Ott

We study what changes to an agent's decision problem increase her value for information. We prove that information becomes more valuable if and only if the agent's reduced-form payoff in her belief becomes more convex. When the…

Theoretical Economics · Economics 2026-04-17 Mark Whitmeyer

Integrating information gained by observing others via Social Bayesian Learning can be beneficial for an agent's performance, but can also enable population wide information cascades that perpetuate false beliefs through the agent…

Multiagent Systems · Computer Science 2014-06-05 Christoph Salge , Daniel Polani

Aging is analyzed as the spontaneous loss of adaptivity and increase in fragility that characterizes dynamic systems. Cybernetics defines the general regulatory mechanisms that a system can use to prevent or repair the damage produced by…

Other Quantitative Biology · Quantitative Biology 2014-04-08 Francis Heylighen

We consider an information update system where an information receiver requests updates from an information provider in order to minimize its age of information. The updates are generated at the transmitter as a result of completing a set…

Information Theory · Computer Science 2019-12-30 Melih Bastopcu , Sennur Ulukus

All biological and artificial agents must learn and make decisions given limits on their ability to process information. As such, a general theory of adaptive behavior should be able to account for the complex interactions between an…

Machine Learning · Computer Science 2023-05-08 Dilip Arumugam , Mark K. Ho , Noah D. Goodman , Benjamin Van Roy

This paper studies sequential information acquisition by an ambiguity-averse decision maker (DM), who decides how long to collect information before taking an irreversible action. The agent optimizes against the worst-case belief and…

Theoretical Economics · Economics 2023-10-06 Sarah Auster , Yeon-Koo Che , Konrad Mierendorff

Many biological phenomena or social events critically depend on how information evolves in complex networks. However, a general theory to characterize information evolution is yet absent. Consequently, numerous unknowns remain about the…

Biological Physics · Physics 2022-07-20 Yang Tian , Guoqi Li , Pei Sun

An analyst observes an agent take a sequence of actions. The analyst does not have access to the agent's information and ponders whether the observed actions could be justified through a rational Bayesian model with a known utility…

Theoretical Economics · Economics 2025-04-08 Henrique de Oliveira , Rohit Lamba

The concept of updating a probability distribution in the light of new evidence lies at the heart of statistics and machine learning. Pearl's and Jeffrey's rule are two natural update mechanisms which lead to different outcomes, yet the…

Logic in Computer Science · Computer Science 2024-02-14 Bart Jacobs , Dario Stein

Common sense suggests that when individuals explain why they believe something, we can arrive at more accurate conclusions than when they simply state what they believe. Yet, there is no known mechanism that provides incentives to elicit…

Computer Science and Game Theory · Computer Science 2025-02-20 Siddarth Srinivasan , Ezra Karger , Michiel Bakker , Yiling Chen

This study extends Blackwell's (1953) comparison of information to a sequential social learning model, where agents make decisions sequentially based on both private signals and the observed actions of others. In this context, we introduce…

Theoretical Economics · Economics 2025-03-27 Hiroto Sato , Konan Shimizu

In this paper we formulate the problem of inference under incomplete information in very general terms. This includes modelling the process responsible for the incompleteness, which we call the incompleteness process. We allow the process…

Artificial Intelligence · Computer Science 2014-01-16 Marco Zaffalon , Enrique Miranda

Informed and robust decision making in the face of uncertainty is critical for robots that perform physical tasks alongside people. We formulate this as Bayesian Reinforcement Learning over latent Markov Decision Processes (MDPs). While…

Robotics · Computer Science 2020-02-11 Gilwoo Lee , Brian Hou , Sanjiban Choudhury , Siddhartha S. Srinivasa

Reinforcement learning in complex environments may require supervision to prevent the agent from attempting dangerous actions. As a result of supervisor intervention, the executed action may differ from the action specified by the policy.…

Artificial Intelligence · Computer Science 2021-07-01 Eric D. Langlois , Tom Everitt

A model of Boolean agents competing in a market is presented where each agent bases his action on information obtained from a small group of other agents. The agents play a competitive game that rewards those in the minority. After a long…

Statistical Mechanics · Physics 2009-10-31 Maya Paczuski , Kevin E. Bassler , Alvaro Corral

This paper proposes a method to construct an adaptive agent that is universal with respect to a given class of experts, where each expert is an agent that has been designed specifically for a particular environment. This adaptive control…

Artificial Intelligence · Computer Science 2010-04-13 Pedro A. Ortega , Daniel A. Braun

This paper presents a new proof of the renewal theorem by bijecting a general point process to a deterministic one (where the time between events is always fixed). It also provides insight into the workings of the renewal theorem.

Probability · Mathematics 2021-08-03 Rohit Pandey
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