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Tomohiro Harada
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2020 – today
- 2024
- [j12]Junya Hoshino, Yuuki Itoh, Ryuma Saotome, Tomohiro Harada, Kenji Matsuda, Tenta Suzuki, Mao Tobisawa, Kaito Kumagae, Johei Matsuoka, Toshinori Kagawa, Kiyohiko Hattori:
Interchange flow control with dynamic obstacles optimized using genetic algorithms - a concept of virtual walls. Artif. Life Robotics 29(2): 230-241 (2024) - [j11]Tomohiro Harada
:
Parallel cooperative multiobjective coevolutionary algorithm for constrained multiobjective optimization problems. Appl. Soft Comput. 153: 111290 (2024) - [j10]Kenji Matsuda, Tenta Suzuki, Tomohiro Harada
Hierarchical Reward Model of Deep Reinforcement Learning for Enhancing Cooperative Behavior in Automated Driving. J. Adv. Comput. Intell. Intell. Informatics 28(2): 431-443 (2024) - [c81]Yuki Hanawa, Tomohiro Harada, Yukiya Miura:
Analysis of the Impact of Prediction Accuracy on Search Performance in Surrogate-assisted Evolutionary Algorithms. CEC 2024: 1-8 - [c80]Tomohiro Harada, Enrique Alba, Gabriel Luque:
Energy and Quality of Surrogate-Assisted Search Algorithms: a First Analysis. CEC 2024: 1-8 - [c79]Akito Takenaka, Tomohiro Harada, Yukiya Miura, Kiyohiko Hattori, Johei Matuoka:
Cooperative Autonomous Driving Control among Vehicles of Different Sizes Using Deep Reinforcement Learning. IJCNN 2024: 1-8 - 2023
- [j9]Tomohiro Harada, Johei Matsuoka, Kiyohiko Hattori:
Behavior analysis of emergent rule discovery for cooperative automated driving using deep reinforcement learning. Artif. Life Robotics 28(1): 31-42 (2023) - [j8]Tomohiro Harada, Sohei Kino, Ruck Thawonmas:
Investigating the influence of survival selection and fitness estimation method in genotype-based surrogate-assisted genetic programming. Artif. Life Robotics 28(1): 181-191 (2023) - [c78]Hitomi Kano
Hybrid Rocket Engine Design Using Pairwise Ranking Surrogate-assisted Differential Evolution. GECCO Companion 2023: 1956-1962 - [c77]Reo Nakaya, Tomohiro Harada, Yukiya Miura, Kiyohiko Hattori, Johei Matsuoka:
Emergence of Cooperative Automated Driving Control at Roundabouts Using Deep Reinforcement Learning. SICE 2023: 97-102 - 2022
- [j7]Tomohiro Harada
A fresh approach to evaluate performance in distributed parallel genetic algorithms. Appl. Soft Comput. 119: 108540 (2022) - [j6]Tomohiro Harada
Comparison of synchronous and asynchronous parallelization of extreme surrogate-assisted multi-objective evolutionary algorithm. Nat. Comput. 21(2): 187-217 (2022) - [c76]Takuya Hakoishi, Tomohiro Harada, Yukiya Miura:
Improving Data Sampling Efficiency of Sensitivity Analysis Based on Bilevel Multi-objective Evolutionary Algorithm. SCIS/ISIS 2022: 1-6 - [c75]Hitomi Kano, Tomohiro Harada, Yukiya Miura:
Differential Evolution Using Surrogate Model Based on Pairwise Ranking Estimation for Constrained Optimization Problems. SCIS/ISIS 2022: 1-6 - 2021
- [j5]Tomohiro Harada
Parallel Genetic Algorithms: A Useful Survey. ACM Comput. Surv. 53(4): 86:1-86:39 (2021) - [c74]Koki Tsujino, Tomohiro Harada, Ruck Thawonmas:
Adaptation of Search Generations in Extreme Learning Assisted MOEA/D Based on Estimation Accuracy of Surrogate Model. CEC 2021: 1519-1526 - [c73]Hayato Noguchi, Tomohiro Harada
Parallel differential evolution applied to interleaving generation with precedence evaluation of tentative solutions. GECCO 2021: 706-713 - [i6]Tomohiro Harada, Enrique Alba, Gabriel Luque:
A Fresh Approach to Evaluate Performance in Distributed Parallel Genetic Algorithms. CoRR abs/2106.09922 (2021) - [i5]Tomohiro Harada:
A Frequency-based Parent Selection for Reducing the Effect of Evaluation Time Bias in Asynchronous Parallel Multi-objective Evolutionary Algorithms. CoRR abs/2107.12053 (2021) - 2020
- [j4]Tomohiro Harada
Analysis of semi-asynchronous multi-objective evolutionary algorithm with different asynchronies. Soft Comput. 24(4): 2917-2939 (2020) - [c72]Tomohiro Harada
Proposal of Multimodal Program optimization Benchmark and Its Application to Multimodal Genetic Programming. CEC 2020: 1-8 - [c71]Sohei Kino, Tomohiro Harada, Ruck Thawonmas:
Proposal of Surrogate Model for Genetic Programming Based on Program Structure Similarity. SICE 2020: 808-813 - [c70]Koki Tsujino, Tomohiro Harada, Ruck Thawonmas:
Analysis of Relation between Prediction Accuracy of Surrogate Model and Search Performance on Extreme Learning Machine Assisted MOEA/D. SICE 2020: 820-825 - [c69]Hayato Noguchi, Akari Sonoda, Tomohiro Harada, Ruck Thawonmas:
Interleaving Generation Evolutionary Algorithm with Precedence Evaluation of Tentative Offspring. SICE 2020: 832-837 - [c68]Tomohiro Harada
Search Progress Dependent Parent Selection for Avoiding Evaluation Time Bias in Asynchronous Parallel Multi-Objective Evolutionary Algorithms. SSCI 2020: 1013-1020 - [c67]Tomohiro Harada
A Study on Efficient Asynchronous Parallel Multi-objective Evolutionary Algorithm with Waiting Time Limitation. TPNC 2020: 121-132
2010 – 2019
- 2019
- [c66]Changeun Yang, Pujana Paliyawan, Ruck Thawonmas, Tomohiro Harada:
TGIF!: Selecting the most healing TNT by optical flow. AAAI Spring Symposium: Interpretable AI for Well-being 2019 - [c65]Febri Abdullah
An Angry Birds Level Generator with Rube Goldberg Machine Mechanisms. CoG 2019: 1-8 - [c64]Ryota Ishii, Suguru Ito, Ruck Thawonmas, Tomohiro Harada
A Fighting Game AI Using Highlight Cues for Generation of Entertaining Gameplay. CoG 2019: 1-6 - [c63]Takahiro Kusano, Yunshi Liu, Pujana Paliyawan, Ruck Thawonmas, Tomohiro Harada
Motion Gaming AI using Time Series Forecasting and Dynamic Difficulty Adjustment. CoG 2019: 1-6 - [c62]Junjie Xu, Pujana Paliyawan, Ruck Thawonmas, Tomohiro Harada
Player Dominance Adjustment: Promoting Self-Efficacy and Experience of Game Players by Adjusting Dominant Power. GCCE 2019: 487-488 - [c61]Ryota Ishii, Ruck Thawonmas, Tomohiro Harada
An Analysis of Highlight-Oriented AI Using Fighting-Game Experience. GCCE 2019: 551-552 - [c60]Sunee Sae-Lao, Pujana Paliyawan, Ruck Thawonmas, Tomohiro Harada
Enhance Physical and Mental Well-Being of Game Players in an Endless Running Game. GCCE 2019: 945-946 - [c59]Zhou Fang, Pujana Paliyawan, Ruck Thawonmas, Tomohiro Harada
Towards an Angry-Birds-Like Game System for Promoting Mental Well-Being of Players using Art-Therapy-Embedded Procedural Content Generation. GCCE 2019: 947-948 - [c58]Shubu Yoshida, Tomohiro Harada
Multimodal genetic programming using program similarity measurement and its application to wall-following problem. GECCO (Companion) 2019: 356-357 - [c57]Yunshi Liu, Febri Abdullah
Improving Brain Memory through Gaming Using Hand Clenching and Spreading. MIG 2019: 42:1-42:3 - [c56]Junjie Xu, Pujana Paliyawan, Yiming Zhang, Ruck Thawonmas, Tomohiro Harada
Player Dominance Adjustment Motion Gaming AI for Health Promotion. MIG 2019: 43:1-43:2 - [c55]Jingdi Xu, Yuuki Okido, Sunee Sae-Lao, Pujana Paliyawan, Ruck Thawonmas, Tomohiro Harada
Promoting Emotional Well-Being with Angry-Birds-like Gameplay on Pixel Image Levels. SeGAH 2019: 1-4 - [i4]Zhou Fang, Pujana Paliyawan, Ruck Thawonmas, Tomohiro Harada:
Towards An Angry-Birds-like Game System for Promoting Mental Well-being of Players Using Art-Therapy-embedded PCG. CoRR abs/1911.02695 (2019) - 2018
- [c54]Yunshi Liu, Pujana Paliyawan, Takahiro Kusano, Tomohiro Harada, Ruck Thawonmas:
A Personalized Method for Calorie Consumption Assessment. AAAI Spring Symposia 2018 - [c53]Yusuke Tajima, Akinori Murata, Tomohiro Harada, Keiki Takadama:
Sleep Stage Re-Estimation Method According To Sleep Cycle Change. AAAI Spring Symposia 2018 - [c52]Makoto Ishihara, Suguru Ito, Ryota Ishii, Tomohiro Harada
Monte-Carlo Tree Search for Implementation of Dynamic Difficulty Adjustment Fighting Game AIs Having Believable Behaviors. CIG 2018: 1-8 - [c51]Ryota Ishii, Suguru Ito, Makoto Ishihara, Tomohiro Harada
Monte-Carlo Tree Search Implementation of Fighting Game AIs Having Personas. CIG 2018: 1-8 - [c50]Yoshina Takano, Wenwen Ouyang, Suguru Ito, Tomohiro Harada
Applying Hybrid Reward Architecture to a Fighting Game AI. CIG 2018: 1-4 - [c49]Jingdi Xu, Changeun Yang, Yuuki Okido, Pujana Paliyawan, Ruck Thawonmas, Tomohiro Harada
An Angry Birds-like Game System for Promoting Players' Emotion. GCCE 2018: 159-160 - [c48]Ryota Ishii, Suguru Ito, Ruck Thawonmas, Tomohiro Harada
An Analysis of Fighting Game AIs Having a Persona. GCCE 2018: 590-591 - [c47]Yoshina Takano, Suguru Ito, Tomohiro Harada
Utilizing Multiple Agents for Decision Making in a Fighting Game. GCCE 2018: 594-595 - [c46]Yuntian Ma, Enzhi Zhang, Koki Tsujino, Tomohiro Harada
An Object Matrix Input Format for a Deep AI in Angry Birds and the Like. GCCE 2018: 596-598 - [c45]Changeun Yang, Pujana Paliyawan, Tomohiro Harada
Blow Up Depression with In-Game TNTs. GCCE 2018: 820-821 - [c44]Hiro Ohtsuka, Misaki Kaidan, Tomohiro Harada
Evolutionary algorithm using surrogate assisted model for simultaneous design optimization benchmark problem of multiple car structures. GECCO (Companion) 2018: 55-56 - [c43]Tomohiro Harada
Crowding distance based promising solution selection in surrogate assisted asynchronous multi-objective evolutionary algorithm. GECCO (Companion) 2018: 253-254 - [c42]Tomohiro Harada
Adaptive asynchrony in semi-asynchronous evolutionary algorithm based on performance prediction using search history. GECCO 2018: 1031-1038 - [c41]Satoko Abiko, Tomohiro Harada, Tadahiro Hasegawa, Shin'ichi Yuta, Naohiro Shimaji:
Semi-autonomous Collision Avoidance Flight Using Two Dimensional Laser Range Finder with Mirrors for Bridge Inspection. ROBIO 2018: 2268-2272 - [c40]Kei Murano, Shubu Yoshida, Tomohiro Harada
A Study on Multimodal Genetic Programming Introducing Program Simplification. SCIS&ISIS 2018: 109-114 - [i3]Yunshi Liu, Pujana Paliyawan, Takahiro Kusano, Tomohiro Harada, Ruck Thawonmas:
A Personalized Method for Calorie Consumption Assessment. CoRR abs/1802.03852 (2018) - 2017
- [j3]Tung Duc Nguyen, Ayumu Shinya, Tomohiro Harada
Segmentation Mask Refinement Using Image Transformations. IEEE Access 5: 26409-26418 (2017) - [j2]Tomohiro Harada
Machine-Code Program Evolution by Genetic Programming Using Asynchronous Reference-Based Evaluation Through Single-Event Upset in On-Board Computer. J. Robotics Mechatronics 29(5): 808-818 (2017) - [c39]Shubu Yoshida, Tomohiro Harada
Multimodal genetic programming by using tree structure similarity clustering. IWCIA 2017: 85-90 - [c38]Kazuki Mori, Suguru Ito, Tomohiro Harada
Feature extraction of gameplays for similarity calculation in gameplay recommendation. IWCIA 2017: 171-176 - [c37]Ruck Thawonmas, Tomohiro Harada:
AI for Game Spectators: Rise of PPG. AAAI Workshops 2017 - [c36]Tomohiro Harada, Takahiro Kawashima, Morito Morishima, Keiki Takadama:
Improving Accuracy of Real-Time Sleep Stage Estimation by Considering Personal Sleep Feature and Rapid Change of Sleep Behavior. AAAI Spring Symposia 2017 - [c35]Pujana Paliyawan, Takahiro Kusano, Yuto Nakagawa, Tomohiro Harada, Ruck Thawonmas:
Adaptive Motion Gaming AI for Health Promotion. AAAI Spring Symposia 2017 - [c34]Yusuke Tajima, Tomohiro Harada, Keiki Takadama:
Sleep Stage Estimation Based on Appriximate Heartrate Calculated from Other Persons. AAAI Spring Symposia 2017 - [c33]Tomohiro Harada
Performance comparison of parallel asynchronous multi-objective evolutionary algorithm with different asynchrony. CEC 2017: 1215-1222 - [c32]Yuxuan Jiang, Tomohiro Harada
Procedural generation of angry birds fun levels using pattern-struct and preset-model. CIG 2017: 154-161 - [c31]Jorge Arturo Moran Bravo, Pujana Paliyawan, Tomohiro Harada
Intelligent assistant for providing instructions and recommending motions during full-body motion gaming. GCCE 2017: 1-2 - [c30]Takahiro Kusano, Pujana Paliyawan, Tomohiro Harada
Towards adaptive motion gaming AI with player's behavior modeling for health promotion. GCCE 2017: 1-2 - [c29]Tomohiro Harada
A study of self-adaptive semi-asynchronous evolutionary algorithm on multi-objective optimization problem. GECCO (Companion) 2017: 1812-1819 - [c28]Misaki Kaidan, Tomohiro Harada
Integrating surrogate evaluation model and asynchronous evolution in multi-objective evolutionary algorithm for expensive and different evaluation time. GECCO (Companion) 2017: 1833-1840 - [i2]Pujana Paliyawan, Takahiro Kusano, Yuto Nakagawa, Tomohiro Harada, Ruck Thawonmas:
Adaptive Motion Gaming AI for Health Promotion. CoRR abs/1704.00961 (2017) - 2016
- [c27]Makoto Ishihara, Taichi Miyazaki, Chun Yin Chu, Tomohiro Harada
Applying and Improving Monte-Carlo Tree Search in a Fighting Game AI. ACE 2016: 27:1-27:6 - [c26]Tomohiro Harada, Fumito Uwano, Takahiro Komine, Yusuke Tajima, Takahiro Kawashima, Morito Morishima, Keiki Takadama:
Real-Time Sleep Stage Estimation from Biological Data with Trigonometric Function Regression Model. AAAI Spring Symposia 2016 - [c25]Misaki Kaidan, Tomohiro Harada
Procedural generation of angry birds levels with adjustable difficulty. CEC 2016: 1311-1316 - [c24]Chun Yin Chu, Suguru Ito, Tomohiro Harada
Position-based reinforcement learning biased MCTS for General Video Game Playing. CIG 2016: 1-8 - [c23]Suguru Ito, Zikun Guo, Chun Yin Chu, Tomohiro Harada
Efficient implementation of breadth first search for general video game playing. GCCE 2016: 1-2 - [c22]Shubu Yoshida, Makoto Ishihara, Taichi Miyazaki, Yuto Nakagawa, Tomohiro Harada
Application of Monte-Carlo tree search in a fighting game AI. GCCE 2016: 1-2 - [c21]Yusuke Tajima, Tomohiro Harada
Personalized Real-Time Sleep Stage from Past Sleep Data to Today's Sleep Estimation. HCI (5) 2016: 501-510 - [c20]Kazuki Mori, Tung Nguyen, Tomohiro Harada
An Improvement of Matrix Factorization with Bound Constraints for Recommender Systems. IIAI-AAI 2016: 103-106 - [i1]Yuxuan Jiang, Misaki Kaidan, Chun Yin Chu, Tomohiro Harada, Ruck Thawonmas:
Procedural Generation of Angry Birds Levels using Building Constructive Grammar with Chinese-Style and/or Japanese-Style Models. CoRR abs/1604.07906 (2016) - 2015
- [c19]Keiki Takadama, Yusuke Tajima, Tomohiro Harada, Atsushi Ishihara, Morito Morishima:
Towards Ambient Intelligence System for Good Sleep By Sound Adjusted to Heartbeat and Respiration. AAAI Spring Symposia 2015 - [c18]Takuma Fujitsuka, Tomohiro Harada
Sightseeing plan recommendation system using sequential pattern mining based on adjacent activities. ASCC 2015: 1-6 - [c17]Ryo Takano, Hiroyuki Sato, Tomohiro Harada
Toward robustness against environmental change speed by artificial bee colony algorithm based on local information sharing. CEC 2015: 1424-1431 - [c16]Chun Yin Chu, Hisaaki Hashizume, Zikun Guo, Tomohiro Harada
Combining pathfmding algorithm with Knowledge-based Monte-Carlo tree search in general video game playing. CIG 2015: 523-529 - [c15]Supaphon Kamon, Tung Duc Nguyen, Tomohiro Harada
Improving heuristic search for RTS-game unit micromanagement using reinforcement learning. GCCE 2015: 25-26 - [c14]Makoto Ishihara, Taichi Miyazaki, Pujana Paliyawan, Chun Yin Chu, Tomohiro Harada
Investigating Kinect-based fighting game AIs that encourage their players to use various skills. GCCE 2015: 334-335 - [c13]Yuto Nakagawa, Kaito Yamamoto, Chun Yin Chu, Tomohiro Harada
Predicting the opponent's action using the k-nearest neighbor algorithm and a substring tree structure. GCCE 2015: 533-534 - [c12]Misaki Kaidan, Chun Yin Chu, Tomohiro Harada
Procedural generation of angry birds levels that adapt to the player's skills using genetic algorithm. GCCE 2015: 535-536 - [c11]Shingo Tomura, Tomohiro Harada
Estimating surrounding symptom level of dementia patient by sleep stage. ISMICT 2015: 190-194 - 2014
- [c10]Yusuke Tajima, Masaya Nakata, Tomohiro Harada, Keiji Sato, Keiki Takadama:
Sleep Stage Estimation Using Synthesized Data of Heart Rate and Body Movement. AAAI Spring Symposia 2014 - [c9]Tomohiro Harada, Keiki Takadama:
Asynchronous Evolution by Reference-Based Evaluation: Tertiary Parent Selection and Its Archive. EuroGP 2014: 198-209 - [c8]Tomohiro Harada
Asynchronously evolving solutions with excessively different evaluation time by reference-based evaluation. GECCO 2014: 911-918 - [c7]Asami Mori, Tomohiro Harada
Favor Information Presentation and Its Effect for Collective-Adaptive Situation. HCI (13) 2014: 455-466 - [c6]Keiki Takadama, Tomohiro Harada
What is Needed to Promote an Asynchronous Program Evolution in Genetic Programing? LION 2014: 227-241 - 2013
- [c5]Tomohiro Harada, Keiki Takadama:
Analyzing Program Evolution in Genetic Programming using Asynchronous Evaluation. ECAL 2013: 713-720 - [c4]Tomohiro Harada
Asynchronous Evaluation Based Genetic Programming: Comparison of Asynchronous and Synchronous Evaluation and Its Analysis. EuroGP 2013: 241-252 - [c3]Keiki Takadama, Yuya Sawadaishi, Tomohiro Harada
Towards Understanding of Relationship among Pareto Optimal Solutions in Multi-dimensional Space via Interactive System. HCI (15) 2013: 137-146 - 2012
- [c2]Tomohiro Harada
Evolving conditional branch programs in Tierra-based Asynchronous Genetic Programming. SCIS&ISIS 2012: 1023-1028 - 2011
- [j1]Tomohiro Harada
Robustness to Bit Inversion in Registers and Acceleration of Program Evolution in On-Board Computer. J. Adv. Comput. Intell. Intell. Informatics 15(8): 1175-1185 (2011) - [c1]Tomohiro Harada
Adaptive mutation depending on program size in asynchronous program evolution. NaBIC 2011: 433-438
Coauthor Index
[j8] [j6] [c74] [c73] [c72] [c71] [c70] [c69] [c66] [c65] [c64] [c63] [c62] [c61] [c60] [c59] [c58] [c57] [c56] [c55] [i4] [c54] [c52] [c51] [c50] [c49] [c48] [c47] [c46] [c45] [c44] [c43] [c40] [i3] [j3] [c39] [c38] [c37] [c35] [c32] [c31] [c30] [c28] [i2] [c27] [c25] [c24] [c23] [c22] [c20] [i1] [c16] [c15] [c14] [c13] [c12]
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