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2020 – today
- 2024
[j2]Jiahao Li
, Tianhan Gao, Qingwei Mi:
Phasic parallel-network policy: a deep reinforcement learning framework based on action correlation. Computing 106(10): 3335-3352 (2024)- [c8]Qingwei Mi, Tianhan Gao:
Novel Dynamic Difficulty Adjustment Methods for Niche Games. IMIS 2024: 189-200 - 2023
- [c7]Qingwei Mi, Tianhan Gao:
General Dynamic Difficulty Adjustment System for Major Game Genres. IMIS 2023: 189-200 - [c6]Baicheng Chen, Tianhan Gao, Qingwei Mi:
An Approach to Optimize Replay Buffer in Value-Based Reinforcement Learning. SoSE 2023: 1-5 - 2022
- [j1]Qingwei Mi, Tianhan Gao:
Adaptive rubber-banding system of dynamic difficulty adjustment in racing games. J. Int. Comput. Games Assoc. 44(1): 18-38 (2022) - [c5]Tianhan Gao, Jin Zhang, Qingwei Mi:
Procedural Generation of Game Levels and Maps: A Review. ICAIIC 2022: 50-55 - [c4]Tianhan Gao, Baicheng Chen, Qingwei Mi:
A Survey of Markov Model in Reinforcement Learning. ICAIIC 2022: 284-287 - [c3]Qingwei Mi, Tianhan Gao:
3D Reconstruction Based on the Depth Image: A Review. IMIS 2022: 172-183 - [c2]Jin Zhang, Tianhan Gao, Qingwei Mi:
Side-Scrolling Platform Game Levels Reachability Repair Method and Its Applications to Super Mario Bros. RIVF 2022: 232-237
2010 – 2019
- 2019
- [c1]Tianhan Gao, Qingwei Mi:
Enemy Attack Management Algorithm for Action Role-Playing Games. BWCCA 2019: 315-326
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