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Title: Faster No-Regret Learning Dynamics for Extensive-Form Correlated and Coarse Correlated Equilibria
Award ID(s):
1901403
NSF-PAR ID:
10392522
Author(s) / Creator(s):
; ; ; ;
Date Published:
Journal Name:
AAAI-22 Reinforcement Learning in Games (RLG) Workshop
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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  1. ABSTRACT

    We show that the Platinum gamma-ray burst (GRB) data compilation, probing the redshift range 0.553 ≤ z ≤ 5.0, obeys a cosmological-model-independent three-parameter Fundamental Plane (Dainotti) correlation and so is standardizable. While they probe the largely unexplored z ∼ 2.3–5 part of cosmological redshift space, the GRB cosmological parameter constraints are consistent with, but less precise than, those from a combination of baryon acoustic oscillation (BAO) and Hubble parameter [H(z)] data. In order to increase the precision of GRB-only cosmological constraints, we exclude common GRBs from the larger Amati-correlated A118 data set composed of 118 GRBs and jointly analyse the remaining 101 Amati-correlated GRBs with the 50 Platinum GRBs. This joint 151 GRB data set probes the largely unexplored z ∼ 2.3–8.2 region; the resulting GRB-only cosmological constraints are more restrictive, and consistent with, but less precise than, those from H(z)  + BAO data.

     
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