works on
decentralized learning 1pac learning 1private information 1reachability objectives 1turn-based stochastic games 1

From the 1 of 6 linked papers with an AI index.

collaborators
Showing cs.CCShow all

1 paper · 1 filter

cs.CC2025

Revealing POMDPs: Qualitative and Quantitative Analysis for Parity Objectives

Ali Asadi, Krishnendu Chatterjee, David Lurie +1

Partially observable Markov decision processes (POMDPs) are a central model for uncertainty in sequential decision making. The most basic objective is the reachability objective, w…