DASA: Delay-Adaptive Multi-Agent Stochastic Approximation

no code implementations • 25 Mar 2024 • Nicolo Dal Fabbro, Arman Adibi, H. Vincent Poor, Sanjeev R. Kulkarni, Aritra Mitra, George J. Pappas

We consider a setting in which $N$ agents aim to speedup a common Stochastic Approximation (SA) problem by acting in parallel and communicating with a central server.

Avg Q-Learning +1

Stochastic Approximation with Delayed Updates: Finite-Time Rates under Markovian Sampling

no code implementations • 19 Feb 2024 • Arman Adibi, Nicolo Dal Fabbro, Luca Schenato, Sanjeev Kulkarni, H. Vincent Poor, George J. Pappas, Hamed Hassani, Aritra Mitra

Motivated by applications in large-scale and multi-agent reinforcement learning, we study the non-asymptotic performance of stochastic approximation (SA) schemes with delayed updates under Markovian sampling.

Avg Multi-agent Reinforcement Learning +1