Deep reinforcement learning (RL) has led to many recent and groundbreaking advances.
However, these advances have often come at the cost of both increased scale in the …

Population-based multi-agent reinforcement learning (PB-MARL) encompasses a range of
methods that merge dynamic population selection with multi-agent reinforcement learning …

Towards Multi-cloud Access Transparency in Serverless Computing Page 1 0740-7459 (c)
2020 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission …

For many years, the distributed systems community has struggled to smooth the transition
from local to remote computing. Transparency means concealing the complexities of …

Access transparency means that both local and remote resources are accessed using
identical operations. With transparency, unmodified single-machine applications could run …

The ever-growing complexity of reinforcement learning (RL) tasks demands a distributed
system to efficiently generate and process a massive amount of data. However, existing …

Deep Reinforcement Learning (DRL) achieves great success in various domains.
Communication in today's DRL algorithms takes non-negligible time compared to the …

As Artificial Intelligence-based applications become more and more complex, speeding up
the learning phase (which is typically computation-intensive) becomes more and more …

Research on Transparent Access Technology of Government Big Data Page 1 Tehnički
vjesnik 31, 3(2024), 715-725 715 ISSN 1330-3651 (Print), ISSN 1848-6339 (Online) https://doi.org/10.17559/TV-20230630000775 …

❖ Rui Wang is a Senior Research Scientist at Uber AI. His research interests include
evolutionary algorithms,, complex systems, evolutionary robotics, reinforcement learning …