3 papers
math.OC2024
Reinforcement Learning for Jointly Optimal Coding and Control Policies for a Controlled Markovian System over a Communication Channel
Evelyn Hubbard, Liam Cregg, Serdar Yüksel
We study the problem of joint optimization involving coding and control policies for a controlled Markovian sytem over a finite-rate noiseless communication channel. While structur…
cs.IT2023
Reinforcement Learning for Near-Optimal Design of Zero-Delay Codes for Markov Sources
Liam Cregg, Tamas Linder, Serdar Yuksel
In the classical lossy source coding problem, one encodes long blocks of source symbols that enables the distortion to approach the ultimate Shannon limit. Such a block-coding appr…
math.OC2023
Sliding Window Codes: Near-Optimality and Q-Learning for Zero-Delay Coding
Liam Cregg, Fady Alajaji, Serdar Yuksel
We study the problem of zero-delay coding for the transmission of a Markov source over a noisy channel with feedback and present a reinforcement learning solution which is guarante…