2 citations · 3 across the 5 of their papers we have counts for
5 papers
ParMod: A Parallel and Modular Framework for Learning Non-Markovian Tasks
Ruixuan Miao, Xu Lu, Cong Tian +2
The commonly used Reinforcement Learning (RL) model, MDPs (Markov Decision Processes), has a basic premise that rewards depend on the current state and action only. However, many r…
Using Experience Classification for Training Non-Markovian Tasks
Ruixuan Miao, Xu Lu, Cong Tian +2
Unlike the standard Reinforcement Learning (RL) model, many real-world tasks are non-Markovian, whose rewards are predicated on state history rather than solely on the current stat…
A Novel Load Balancing Scheme for Mobile Edge Computing
Zhenhua Duan, Cong Tian, Nan Zhang +5
To overcome long propagation delays for data exchange between the remote cloud data center and end devices in Mobile Cloud Computing (MCC), Mobile Edge Computing (MEC) is merging t…
Buchi Determinization Made Tighter
Cong Tian, Zhenhua Duan
By separating the principal acceptance mechanism from the concrete acceptance condition of a given Büchi automaton with states,Schewe presented the construction of an equivalen…
Making Abstraction Refinement Efficient in Model Checking
Cong Tian, Zhenhua Duan
Abstraction is one of the most important strategies for dealing with the state space explosion problem in model checking. In the abstract model, although the state space is largely…