3 papers
q-fin.TR2021
TradeR: Practical Deep Hierarchical Reinforcement Learning for Trade Execution
Karush Suri, Xiao Qi Shi, Konstantinos Plataniotis +1
Advances in Reinforcement Learning (RL) span a wide variety of applications which motivate development in this area. While application tasks serve as suitable benchmarks for real w…
cs.LG2020
Energy-based Surprise Minimization for Multi-Agent Value Factorization
Karush Suri, Xiao Qi Shi, Konstantinos Plataniotis +1
Multi-Agent Reinforcement Learning (MARL) has demonstrated significant success in training decentralised policies in a centralised manner by making use of value factorization metho…
cs.LG2020
Maximum Mutation Reinforcement Learning for Scalable Control
Karush Suri, Xiao Qi Shi, Konstantinos N. Plataniotis +1
Advances in Reinforcement Learning (RL) have demonstrated data efficiency and optimal control over large state spaces at the cost of scalable performance. Genetic methods, on the o…