activity
20202026
most citedResource-Constrained Federated Learning with Heterogeneous Labels and Models

5 citations · 11 across the 10 of their papers we have counts for

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2 papers · 1 filter

cs.AI2026

ASALT: Adaptive State Alignment for Lateral Transfer in Multi-agent Reinforcement Learning

Anurag Akula, Satheesh K. Perepu, Abhishek Sarkar +1

Multi-agent reinforcement learning (MARL) addresses the problem of training multiple agents that pursue collaborative, competitive, or mixed objectives. Prior work has investigated…

cs.AI2023

Goals are Enough: Inducing AdHoc cooperation among unseen Multi-Agent systems in IMFs

Kaushik Dey, Satheesh K. Perepu, Abir Das

Intent-based management will play a critical role in achieving customers' expectations in the next-generation mobile networks. Traditional methods cannot perform efficient resource…