8 citations · 13 across the 5 of their papers we have counts for
5 papers
Approximate Nash Equilibrium Learning for n-Player Markov Games in Dynamic Pricing
Larkin Liu
We investigate Nash equilibrium learning in a competitive Markov Game (MG) environment, where multiple agents compete, and multiple Nash equilibria can exist. In particular, for an…
An Extensible and Modular Design and Implementation of Monte Carlo Tree Search for the JVM
Larkin Liu, Jun Tao Luo
Flexible implementations of Monte Carlo Tree Search (MCTS), combined with domain specific knowledge and hybridization with other search algorithms, can be powerful for finding the…
Algorithm for Two-Phase Facility Planning via Balanced Clustering and Integer Programming
Larkin Liu
We present a solution for a two-phase facility planning scenario where in the first phase, there is some flexibility in determining where the locations of facilities (or sources) s…
Improving the Performance of the LSTM and HMM Model via Hybridization
Larkin Liu, Yu-Chung Lin, Joshua Reid
Language models based on deep neural networks and traditional stochastic modelling have become both highly functional and effective in recent times. In this work, a general survey…
Multi-Armed Bandit Strategies for Non-Stationary Reward Distributions and Delayed Feedback Processes
Larkin Liu, Richard Downe, Joshua Reid
A survey is performed of various Multi-Armed Bandit (MAB) strategies in order to examine their performance in circumstances exhibiting non-stationary stochastic reward functions in…