8 citations · 19 across the 4 of their papers we have counts for
4 papers
Scalable Multi-Agent Model-Based Reinforcement Learning
Vladimir Egorov, Aleksei Shpilman
Recent Multi-Agent Reinforcement Learning (MARL) literature has been largely focused on Centralized Training with Decentralized Execution (CTDE) paradigm. CTDE has been a dominant…
Self-Imitation Learning from Demonstrations
Georgiy Pshikhachev, Dmitry Ivanov, Vladimir Egorov +1
Despite the numerous breakthroughs achieved with Reinforcement Learning (RL), solving environments with sparse rewards remains a challenging task that requires sophisticated explor…
Flatland Competition 2020: MAPF and MARL for Efficient Train Coordination on a Grid World
Florian Laurent, Manuel Schneider, Christian Scheller +24
The Flatland competition aimed at finding novel approaches to solve the vehicle re-scheduling problem (VRSP). The VRSP is concerned with scheduling trips in traffic networks and th…
Balancing Rational and Other-Regarding Preferences in Cooperative-Competitive Environments
Dmitry Ivanov, Vladimir Egorov, Aleksei Shpilman
Recent reinforcement learning studies extensively explore the interplay between cooperative and competitive behaviour in mixed environments. Unlike cooperative environments where a…