27 citations · 29 across the 3 of their papers we have counts for
3 papers
Disentangling Successor Features for Coordination in Multi-agent Reinforcement Learning
Seung Hyun Kim, Neale Van Stralen, Girish Chowdhary +1
Multi-agent reinforcement learning (MARL) is a promising framework for solving complex tasks with many agents. However, a key challenge in MARL is defining private utility function…
Semi-supervised Learning for COVID-19 Image Classification via ResNet
Lucy Nwosu, Xiangfang Li, Lijun Qian +2
Coronavirus disease 2019 (COVID-19) is an ongoing global pandemic in over 200 countries and territories, which has resulted in a great public health concern across the internationa…
Combating the Compounding-Error Problem with a Multi-step Model
Kavosh Asadi, Dipendra Misra, Seungchan Kim +1
Model-based reinforcement learning is an appealing framework for creating agents that learn, plan, and act in sequential environments. Model-based algorithms typically involve lear…