3 citations · 7 across the 6 of their papers we have counts for
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cs.LG2021★ 3 cited
Vision Transformer for Learning Driving Policies in Complex Multi-Agent Environments
Eshagh Kargar, Ville Kyrki
Driving in a complex urban environment is a difficult task that requires a complex decision policy. In order to make informed decisions, one needs to gain an understanding of the l…
cs.LG2021
MACRPO: Multi-Agent Cooperative Recurrent Policy Optimization
Eshagh Kargar, Ville Kyrki
This work considers the problem of learning cooperative policies in multi-agent settings with partially observable and non-stationary environments without a communication channel.…
cs.LG2021
Increasing the Efficiency of Policy Learning for Autonomous Vehicles by Multi-Task Representation Learning
Eshagh Kargar, Ville Kyrki
Driving in a dynamic, multi-agent, and complex urban environment is a difficult task requiring a complex decision-making policy. The learning of such a policy requires a state repr…