3 citations · 4 across the 3 of their papers we have counts for
3 papers
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.RO2020★ 1 cited
Efficient Latent Representations using Multiple Tasks for Autonomous Driving
Eshagh Kargar, Ville Kyrki
Driving in the dynamic, multi-agent, and complex urban environment is a difficult task requiring a complex decision policy. The learning of such a policy requires a state represent…