Optimal Strategies for Decision Theoretic Online Learning

06/20/2021
by   Yoav Freund, et al.
6

We extend the drifting games analysis to continuous time and show that the optimal adversary, if the value function has strictly positive derivative up to fourth order is bronian motion.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
06/01/2022

Continuous Prediction with Experts' Advice

Prediction with experts' advice is one of the most fundamental problems ...
research
06/08/2018

Continuous-time Value Function Approximation in Reproducing Kernel Hilbert Spaces

Motivated by the success of reinforcement learning (RL) for discrete-tim...
research
03/26/2021

On the Time Discretization of the Feynman-Kac Forward-Backward Stochastic Differential Equations for Value Function Approximation

Novel numerical estimators are proposed for the forward-backward stochas...
research
06/28/2023

Continuous-Time q-learning for McKean-Vlasov Control Problems

This paper studies the q-learning, recently coined as the continuous-tim...
research
12/31/2019

The Gambler's Problem and Beyond

We analyze the Gambler's problem, a simple reinforcement learning proble...
research
06/11/2020

Group-Fair Online Allocation in Continuous Time

The theory of discrete-time online learning has been successfully applie...
research
04/25/2023

Suboptimal Controller Synthesis for Cart-Poles and Quadrotors via Sums-of-Squares

Sums-of-squares (SOS) optimization is a promising tool to synthesize cer...

Please sign up or login with your details

Forgot password? Click here to reset