Showing results 1 to 28 of 28
A 0.55 V 1.1 mW Artificial Intelligence Processor With On-Chip PVT Compensation for Autonomous Mobile Robots Kim, Youchang; Shin, Dongjoo; Lee, Jinsu; Lee, Yongsu; Yoo, Hoi-Jun, IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS, v.65, no.2, pp.567 - 580, 2018-02 |
A Framework for Automated Cellular Network Tuning With Reinforcement Learning Mismar, Faris B.; Choi, Jinseok; Evans, Brian L., IEEE TRANSACTIONS ON COMMUNICATIONS, v.67, no.10, pp.7152 - 7167, 2019-10 |
Convergence of Dynamic Programming on the Semidefinite Cone for Discrete-Time Infinite-Horizon LQR Lee, Donghwan, IEEE TRANSACTIONS ON AUTOMATIC CONTROL, v.67, no.10, pp.5661 - 5668, 2022-10 |
Data-driven control design with LMIs and dynamic programming Lee, Donghwan; Kim, Do Wan, IEEE ACCESS, v.11, pp.14309 - 14321, 2023-03 |
Deep Learning-Based Ground Vibration Monitoring: Reinforcement Learning and RNN-CNN Approach Yun, Sangseok; Kang, Jae-Mo; Ha, Jeongseok; Lee, Sangho; Ryu, Dong-Woo; Kwon, Jihoe; Kim, Il-Min, IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, v.19, 2022-01 |
Design of a fuzzy logic controller with Evolutionary Q-Learning Kim, MS; Lee, Ju-Jang, INTELLIGENT AUTOMATION AND SOFT COMPUTING, v.12, no.4, pp.369 - 381, 2006 |
Design of multiobjective fuzzy control system using reinforcement learning = 강화 학습을 이용한 다목적 퍼지 제어 시스템의 설계link Kang, Dong-Oh; 강동오; et al, 한국과학기술원, 2001 |
Energy-Efficient Online Path Planning of Multiple Drones Using Reinforcement Learning Hong, Dooyoung; Lee, Seonhoon; Cho, Young Hoo; Baek, Donkyu; Kim, Jaemin; Chang, Naehyuck, IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, v.70, no.10, pp.9725 - 9740, 2021-10 |
Free-form optimization of nanophotonic devices: from classical methods to deep learning Park, Juho; Kim, Sanmun; Nam, Daniel Wontae; Chung, Haejun; Park, Chan Y.; Jang, Min Seok, NANOPHOTONICS, v.11, no.9, pp.1809 - 1845, 2022-01 |
Hindsight Goal Ranking on Replay Buffer for Sparse Reward Environment![]() Luu, Tung M.; Yoo, Chang-Dong, IEEE ACCESS, v.9, pp.51996 - 52007, 2021-04 |
Humanoid push recovery based on reinforcement learning in continuous state and action space = 연속 상태.행동공간에서 강화학습에 기반한 인간형 로봇의 넘어짐 방지link Mao, Wentao; 모문탁; et al, 한국과학기술원, 2010 |
Incremental Receptive Field Weighted Actor-Critic Lee, Dong-Hyun; Lee, Ju-Jang, IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, v.9, no.1, pp.62 - 71, 2013-02 |
Intellectual Algorithm for Enhancing System Capacity in Cellular and WLAN Coexisting Communication Networks = 셀룰러와 무선 LAN이 공존하는 통신망에서 시스템 용량을 개선하기 위한 지능 알고리즘link Chung, Byung Chang; 정병창; et al, 한국과학기술원, 2017 |
Intelligent Network-on-Chip With Online Reinforcement Learning for Portable HD Object Recognition Processor Park, Jun-Young; Hong, In-Joon; Kim, Gyeong-Hoon; Nam, Byeong-Gyu; Yoo, Hoi-Jun, IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS, v.61, no.2, pp.476 - 484, 2014-02 |
Landing posture control of a robotic cat using fast converging reinforcement learning = 빠르게 수렴하는 강화학습을 이용한 고양이 로봇의 착지자세 제어link Shin, Bong-Gun; 신봉근; et al, 한국과학기술원, 2009 |
Learning-based resource partitioning in heterogeneous networks with multiple network operators Chung, Byung Chang; Cho, Dong-Ho, IEEE COMMUNICATIONS LETTERS, v.25, no.3, pp.869 - 873, 2021-03 |
Modular Q-learning based multi-agent cooperation for robot soccer Park, KH; Kim, YJ; Kim, Jong-Hwan, ROBOTICS AND AUTONOMOUS SYSTEMS, v.35, no.2, pp.109 - 122, 2001-05 |
Optimal Design of Wireless Charging Electric Bus System Based on Reinforcement Learning![]() LEE, HYUKJOON; Ji, Dong Jin; Cho, Dong-Ho, ENERGIES, v.12, no.7, 2019-04 |
Primal-Dual Q-Learning Framework for LQR Design Lee, Donghwan; Hu, Jianghai, IEEE TRANSACTIONS ON AUTOMATIC CONTROL, v.64, no.9, pp.3756 - 3763, 2019-09 |
Reinforcement learning based base station cooperation scheme in mobile networks = 이동망에서 강화 학습을 이용한 기지국 협력 방안link Chung, Byung-Chang; 정병창; et al, 한국과학기술원, 2013 |
Reinforcement Learning-Based Counter Fixed-Wing Drone System Using GNSS Deception Chae, Myoung-Ho; Park, Seong-Ook; Choi, Seung-Ho; Choi, Chae-Taek, IEEE ACCESS, v.12, pp.16549 - 16558, 2024 |
Retro-RL: Reinforcing Nominal Controller with Deep Reinforcement Learning for Tilting-Rotor Drones Nahrendra, I. Made Aswin; Tirtawardhana, Christian; Yu, Byeongho; Lee, Eungchang Mason; Myung, Hyun, IEEE ROBOTICS AND AUTOMATION LETTERS, v.7, no.4, pp.9004 - 9011, 2022-10 |
ReveNAND: A Fast-Drift-Aware Resilient 3D NAND Flash Design Shihab, Mustafa M.; Zhang, Jie; Jung, Myoungsoo; Kandemir, Mahmut, ACM TRANSACTIONS ON ARCHITECTURE AND CODE OPTIMIZATION, v.15, no.2, 2018-06 |
Sample-efficient inverse design of freeform nanophotonic devices with physics-informed reinforcement learning Park, Chaejin; Kim, Sanmun; Jung, Anthony W.; Park, Juho; Seo, Dongjin; Kim, Yongha; Park, Chanhyung; et al, NANOPHOTONICS, v.13, no.8, pp.1483 - 1492, 2024-04 |
Semi-dynamic Cell-Clustering Algorithm Based on Reinforcement Learning in Cooperative Transmission System Chung, Byung Chang; Cho, Dong-Ho, IEEE SYSTEMS JOURNAL, v.12, no.4, pp.3853 - 3856, 2018-12 |
Structural Optimization of a One-Dimensional Freeform Metagrating Deflector via Deep Reinforcement Learning Seo, Dongjin; Nam, Daniel Wontae; Park, Juho; Park, Chan Y.; Jang, Min Seok, ACS PHOTONICS, v.9, no.2, pp.452 - 458, 2021-12 |
Utilizing Skipped Frames in Action Repeats for Improving Sample Efficiency in Reinforcement Learning Luu, Tung M.; Nguyen, Thanh; Vu, Thang; Yoo, Chang-Dong, IEEE ACCESS, v.10, pp.64965 - 64975, 2022 |
강화 학습을 이용한 비전 기반의강인한 손 모양 인식에 대한 연구 장효영; 변증남, 전자공학회논문지 - CI, v.43, no.3, pp.39 - 49, 2006-05 |
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