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Showing results 1 to 15 of 15

1
A dynamic penalty approach to state constraint handling in deep reinforcement learning

Yoo, Haeun; Zavala, Victor M.; Lee, Jay Hyung, JOURNAL OF PROCESS CONTROL, v.115, pp.157 - 166, 2022-07

2
Decision-making in brains and robots - the case for an interdisciplinary approach

Lee, Sang Wan; Seymour, Ben, CURRENT OPINION IN BEHAVIORAL SCIENCES, v.26, pp.137 - 145, 2019-04

3
Deep learned finite elements

Jung, Jaeho; Yoon, Kyungho; Lee, Phill-Seung, COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, v.372, 2020-12

4
Deep reinforcement learning for feedback control in a collective flashing ratchet

Kim, Dong-Kyum; Jeong, Hawoong, PHYSICAL REVIEW RESEARCH, v.3, no.2, 2021-04

5
How to Make AlphaGo's Children Explainable

Park, Woosuk, PHILOSOPHIES, v.7, no.3, 2022-06

6
Hybrid materials of upcycled Mn3O4 and reduced graphene oxide for a buffer layer in organic solar cells

Lee, Cheol-Ho; Lee, Sungho; Yeo, Jun-Seok; Kang, Gil-Seong; Noh, Yong-Jin; Park, Sae-Mi; Lee, Doh Chang; et al, JOURNAL OF INDUSTRIAL AND ENGINEERING CHEMISTRY, v.61, pp.106 - 111, 2018-05

7
Importance of prefrontal meta control in human-like reinforcement learning

Lee, Jee Hang; Leibo, Joel Z.; An, Su Jin; Lee, Sang Wan, FRONTIERS IN COMPUTATIONAL NEUROSCIENCE, v.16, 2022-12

8
K-EmoCon, a multimodal sensor dataset for continuous emotion recognition in naturalistic conversations

Park, Cheul Young; Cha, Narae; Kang, Soowon; Kim, Auk; Khandoker, Ahsan Habib; Hadjileontiadis, Leontios; Oh, Alice; et al, SCIENTIFIC DATA, v.7, no.1, pp.293, 2020-09

9
Monitoring the evolutionary aspect of the Gene Ontology to enhance predictability and usability

Park, Jong Cheol; Kim, Tak Eun; Park, Jinah, BMC BIOINFORMATICS, v.9, no.Suppl 3:S7, 2008-04

10
Polymer Analog Memristive Synapse with Atomic-Scale Conductive Filament for Flexible Neuromorphic Computing System

Jang, Byung Chul; Kim, Seong-Gyu; Yang, SangYoon; Park, Ji-Hun; Cha, Jun-Hwe; Oh, Jungyeop; Choi, Junhwan; et al, NANO LETTERS, v.19, no.2, pp.839 - 849, 2019-02

11
Reinforcement Learning - Overview of recent progress and implications for process control

Shin, Joohyun; Badgwell, Thomas A.; Liu, Kuang-Hung; Lee, Jay Hyung, COMPUTERS & CHEMICAL ENGINEERING, v.127, pp.282 - 294, 2019-08

12
Representation, learning, and planning algorithms for geometric task and motion planning

Kim, Beomjoon; Shimanuki, Luke; Kaelbling, Leslie Pack; Lozano-Perez, Tomas, INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH, v.41, no.2, pp.210 - 231, 2022-02

13
Sampling Rate Decay in Hindsight Experience Replay for Robot Control

Vecchietti, Luiz Felipe; Seo, Minah; Har, Dongsoo, IEEE TRANSACTIONS ON CYBERNETICS, v.52, no.3, pp.1515 - 1526, 2022-03

14
Trunk range of motion: A wearable sensor-based test protocol and indicator of fall risk in older people

Yu, Xiaoqun; Park, Seonghyeok; Xiong, Shuping, APPLIED ERGONOMICS, v.108, 2023-04

15
Two-stage training algorithm for A robot soccer

Kim, Taeyoung; Vecchietti, Luiz Felipe; Choi, Kyujin; Sariel, Sanem; Har, Dongsoo, PEERJ COMPUTER SCIENCE, v.7, 2021-09

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