We propose a fully distributed actor-critic architecture, named Diff-DAC...
Recent policy optimization approaches have achieved substantial empirica...
We consider the problem of adaptively placing sensors along an interval ...
Many real-world systems such as taxi systems, traffic networks and smart...
Although multi-agent reinforcement learning can tackle systems of
strate...
We propose a fully distributed actor-critic algorithm approximated by de...
We propose a multiagent distributed actor-critic algorithm for multitask...
The key challenge in multiagent learning is learning a best response to ...
Game theory's prescriptive power typically relies on full rationality an...