Jinkyoo Park

Assistant Professor

Korea Advanced Institute of Science and Technology

South Korea

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About

Jinkyoo Park is an Assistant Professor at the Korea Advanced Institute of Science and Technology in South Korea. His research areas encompass genetic algorithms, energy trading systems, multi-agent traffic signal control, and various applications of neural networks in optimization problems. Recent articles include works on hierarchical vehicle routing, energy shaping, and learning stochastic optimal policies through advanced machine learning techniques.

Articles (12)

Year:

2025

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2025

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2024

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2024

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2024

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2024

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2022

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2022

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2022

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2021

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2021

Year:

2020

Collaborators (7)

Changhyun Kwon

Associate Professor

KAIST

SOUTH KOREA

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Mykel Kochenderfer

Associate Professor

Stanford University

UNITED STATES

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FEDERICO CALIFANO

University of Twente

NETHERLANDS

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Hajime Asama

University of Tokyo

JAPAN

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Atsushi Yamashita

University of Tokyo

JAPAN

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Lance Manuel

Professor

University of Texas at Austin

UNITED STATES

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Hwasoo Yeo

Professor

Korea Advanced Institute of Science and Technology

SOUTH KOREA

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Jinkyoo Park

Research Interests

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About

Articles (12)

Incentive Design of Shared ESS Energy Trading Game

Decentralized and Communication-Based Multi-Agent Traffic Signal Control Model Employing a Graph Representation for the State

Distributed Online Planning for Min-Max Problems in Networked Markov Games

Interactive Autonomous Navigation With Internal State Inference and Interactivity Estimation

Genetic Algorithms with Neural Cost Predictor for Solving Hierarchical Vehicle Routing Problems

A Neural Separation Algorithm for the Rounded Capacity Inequalities

Learning Stochastic Optimal Policies via Gradient Descent

Optimal Energy Shaping via Neural Approximators

Scalable Inference for Hybrid Bayesian Hidden Markov Model Using Gaussian Process Emission

Learning to schedule job-shop problems: representation and policy learning using graph neural network and reinforcement learning

Cooperative zone-based rebalancing of idle overhead hoist transportations using multi-agent reinforcement learning with graph representation learning

Wind Field-Based Short-Term Turbine Response Forecasting by Stacked Dilated Convolutional LSTMs

Collaborators (7)

Changhyun Kwon

Mykel Kochenderfer

FEDERICO CALIFANO

Hajime Asama

Atsushi Yamashita

Lance Manuel

Hwasoo Yeo

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