Showing results 56 to 75 of 75
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 for robotic flow shop scheduling with processing time variations Lee, Jun-Ho; Kim, Hyun-Jung, INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, v.60, no.7, pp.2346 - 2368, 2022-04 |
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 |
Rewards Prediction-Based Credit Assignment for Reinforcement Learning With Sparse Binary Rewards![]() Seo, Minah; Vecchietti, Luiz Felipe; Lee, Sangkeum; Har, Dongsoo, IEEE ACCESS, v.7, pp.118776 - 118791, 2019-08 |
Role of dopamine D2 receptors in optimizing choice strategy in a dynamic and uncertain environment![]() Kwak, Shinae; Huh, Namjung; Seo, Ji-Seon; Lee, Jung-Eun; Han, Pyung-Lim; Jung, MinWhan, FRONTIERS IN BEHAVIORAL NEUROSCIENCE, v.8, 2014-10 |
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 |
Scheduling PID Attitude and Position Control Frequencies for Time-Optimal Quadrotor Waypoint Tracking under Unknown External Disturbances Kang, Cheongwoong; Park, Bumjin; Choi, Jaesik, SENSORS, v.22, no.1, 2022-01 |
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 |
Simulation-based learning of cost-to-go for control of nonlinear processes Lee, JM; Lee, JayHyung, KOREAN JOURNAL OF CHEMICAL ENGINEERING, v.21, no.2, pp.338 - 344, 2004-03 |
Spatially and temporally extended state space for multilayered reinforcement learning in cognitive developmental robot = 인지 발달 로봇을 위한 다계층 강화학습의 시공간적으로 확장된 상태공간link Yang, Jeong-Yean; 양정연; et al, 한국과학기술원, 2011 |
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 |
Synaptic plasticity model of a spiking neural network for reinforcement learning Lee, K; Kwon, Dong-Soo, NEUROCOMPUTING, v.71, no.13-15, pp.3037 - 3043, 2008-08 |
Transient activation of midbrain dopamine neurons by reward risk. Fiorillo, Christopher D., NEUROSCIENCE, v.197, pp.162 - 171, 2011-12 |
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 |
강화학습에 기반한 이족보행 패턴에 대한 연구 = A study on bipedal walking pattern based on the reinforcement learninglink 한상훈; Sanghoon Han; 김수현; SooHyun Kim; et al, 한국과학기술원, 2015 |
심층 강화학습기반 연속상태공간 제어를 위한 보상 함수 분석 강민구; 김기응, 정보과학회논문지, v.47, no.1, pp.78 - 87, 2020-01 |
제약을 갖는 POMDP를 위한 휴리스틱 검색 가치 반복 알고리즘 = Heuristic search value iteration for constrained POMDPslink 고봉석; Goh, Bong-Seok; et al, 한국과학기술원, 2013 |
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