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Kenshi Abe — most-cited papers & profile · Reinforcement Learning
← authors
·
overview
Kenshi Abe
9
papers ·
13
citations ·
4
h-index
CyberAgent (Japan)
Google Scholar ↗
Semantic Scholar ↗
OpenAlex ↗
Most-cited papers
Off-Policy Exploitability-Evaluation in Two-Player Zero-Sum Markov Games
2020 · 2 citations
Mean-Variance Efficient Reinforcement Learning with Applications to Dynamic Financial Investment
2020 · 1 citations
Policy Testing in Markov Decision Processes
2025
Policy Gradient Algorithms with Monte Carlo Tree Learning for Non-Markov Decision Processes
2022
Why Guided Dialog Policy Learning performs well? Understanding the role of adversarial learning and its alternative
2023
Return-Aligned Decision Transformer
2024
Approximate State Abstraction for Markov Games
2024
Top co-authors
Tetsuro Morimura
· 4
Kaito Ariu
· 2
Alexandre Proutière
· 1
Asahi Hentona
· 1
Atsushi Iwasaki
· 1
Edgar Simo-Serra
· 1
Hiroki Ishibashi
· 1
Hirotaka Ninomiya
· 1
Kazuhiro Ota
· 1
Kei Nakagawa
· 1
Kentaro Baba
· 1
Masahiro Kato
· 1
Topics
Policy Gradient
Game AI
Model-Based RL
Offline RL
Multi-Agent
Exploration
Safe RL
Value-Based
RLHF & Alignment