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Found 4 papers, 3 papers with code
Matrix Encoding Networks for Neural Combinatorial Optimization
A popular approach is to use a neural net to compute on the parameters of a given CO problem and extract useful information that guides the search for good solutions.
POMO: Policy Optimization with Multiple Optima for Reinforcement Learning
We introduce Policy Optimization with Multiple Optima (POMO), an end-to-end approach for building such a heuristic solver.
Cooperative Multi-Agent Reinforcement Learning Framework for Scalping Trading
We explore deep Reinforcement Learning(RL) algorithms for scalping trading and knew that there is no appropriate trading gym and agent examples.
Multi-agent Reinforcement Learning
reinforcement-learning
+1
Clear the Fog: Combat Value Assessment in Incomplete Information Games with Convolutional Encoder-Decoders
StarCraft, one of the most popular real-time strategy games, is a compelling environment for artificial intelligence research for both micro-level unit control and macro-level strategic decision making.
