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2020 – today
- 2023
[j62]Tomoaki Takagi
, Keiki Takadama, Hiroyuki Sato:
Directional Pareto Front and Its Estimation to Encourage Multi-Objective Decision-Making. IEEE Access 11: 20619-20634 (2023)- [c180]Tomoaki Takagi, Keiki Takadama, Hiroyuki Sato:
Pareto Front Upconvert by Iterative Estimation Modeling and Solution Sampling. EMO 2023: 218-230 - 2022
- [c179]Hiroki Shiraishi, Yohei Havamizu, Hiroyuki Sato, Keiki Takadama:
Beta Distribution based XCS Classifier System. CEC 2022: 1-8 - [c178]Tomoaki Takagi, Keiki Takadama, Hiroyuki Sato:
Supervised Multi-Objective Optimization Algorithm Using Estimation. CEC 2022: 1-8 - [c177]Shoichiro Tanaka, Keiki Takadama, Hiroyuki Sato:
Impacts of Single-objective Landscapes on Multi-objective Optimization. CEC 2022: 1-8 - [c176]Naoya Yatsu, Hiroki Shiraishi, Hiroyuki Sato, Keiki Takadama:
XCSR with VAE using Gaussian Distribution Matching: From Point to Area Matching in Latent Space for Less-overlapped Rule Generation in Observation Space. CEC 2022: 1-8 - [c175]Iko Nakari, Naoya Matsuda, Keiki Takadama:
Non-Contact REM Sleep Estimation Correction by Time-Series Confidence of Predictions: From Binary to Continuous Prediction in Machine Learning for Biological Data. EMBC 2022: 1008-1011 - [c174]Naoya Matsuda, Iko Nakari, Keiki Takadama:
Unstable Circadian Rhythm of Heart Rate of Alzheimer Dementia Based on Biological Data of Mattress Sensor. EMBC 2022: 1129-1132 - [c173]Hiroki Shiraishi, Yohei Hayamizu, Iko Nakari, Hiroyuki Sato, Keiki Takadama:
Inheritance vs. Expansion: Generalization Degree of Nearest Neighbor Rule in Continuous Space as Covering Operator of XCS. EvoApplications 2022: 352-368 - [c172]Hiroki Shiraishi, Yohei Hayamizu, Hiroyuki Sato, Keiki Takadama:
Absumption based on overgenerality and condition-clustering based specialization for XCS with continuous-valued inputs. GECCO 2022: 422-430 - [c171]Hiroki Shiraishi, Yohei Hayamizu, Hiroyuki Sato, Keiki Takadama:
Can the same rule representation change its matching area?: enhancing representation in XCS for continuous space by probability distribution in multiple dimension. GECCO 2022: 431-439 - [c170]Fumito Uwano, Daiki Yamane, Keiki Takadama:
Design of Human-Agent-Group Interaction for Correct Opinion Sharing on Social Media. HCI (4) 2022: 146-165 - [c169]Takeru Aoki, Keiki Takadama, Hiroyuki Sato:
Synergistic Effect of Adaptive Synapse Arrangement and Column-based Decoder in Cortical Learning Algorithm. SCIS/ISIS 2022: 1-6 - [c168]Kazushi Fujino, Takeru Aoki, Keiki Takadama, Hiroyuki Sato:
Adaptive Synapse Adjustment for Multivariate Cortical Learning Algorithm. SCIS/ISIS 2022: 1-8 - 2021
- [j61]Takeru Aoki, Keiki Takadama, Hiroyuki Sato:
Adaptive Synapse Arrangement in Cortical Learning Algorithm. J. Adv. Comput. Intell. Intell. Informatics 25(4): 450-466 (2021) - [c167]Yohei Hayamizu, Saeid Amiri, Kishan Chandan, Keiki Takadama, Shiqi Zhang:
Guiding Robot Exploration in Reinforcement Learning via Automated Planning. ICAPS 2021: 625-633 - [c166]Masakazu Tadokoro, Hiroyuki Sato, Keiki Takadama:
XCS with Weight-based Matching in VAE Latent Space and Additional Learning of High-Dimensional Data. CEC 2021: 304-310 - [c165]Hiroki Shiraishi, Masakazu Tadokoro, Yohei Hayamizu, Yukiko Fukumoto, Hiroyuki Sato, Keiki Takadama:
Increasing Accuracy and Interpretability of High-Dimensional Rules for Learning Classifier System. CEC 2021: 311-318 - [c164]Tomoaki Takagi, Keiki Takadama, Hiroyuki Sato:
Weight Vector Arrangement Using Virtual Objective Vectors in Decomposition-based MOEA. CEC 2021: 1462-1469 - [c163]Iko Nakari, Keiki Takadama:
Sleep Apnea Syndrome Detection Based on Degree of Convexity of Logarithmic Spectrum Calculated from Overnight Bio-vibration Data of Mattress Sensor. EMBC 2021: 2270-2273 - [c162]Naoya Matsuda, Iko Nakari, Keiki Takadama:
Alzheimer Dementia Detection Based on Unstable Circadian Rhythm Waves Extracted from Heartrate. EMBC 2021: 4473-4476 - [c161]Tomoaki Takagi, Keiki Takadama, Hiroyuki Sato:
Pareto Front Estimation Using Unit Hyperplane. EMO 2021: 126-138 - [c160]Sho Kajihara, Hiroyuki Sato, Keiki Takadama:
Generating Duplex Routes for Robust Bus Transport Network by Improved Multi-objective Evolutionary Algorithm Based on Decomposition. EvoApplications 2021: 65-80 - [c159]Hiroki Shiraishi, Masakazu Tadokoro, Yohei Hayamizu, Yukiko Fukumoto, Hiroyuki Sato, Keiki Takadama:
Misclassification detection based on conditional VAE for rule evolution in learning classifier system. GECCO Companion 2021: 169-170 - [c158]Yoshimiki Maekawa, Tomohiro Yamaguchi, Keiki Takadama:
Analyzing Early Stage of Forming a Consensus from Viewpoint of Majority/Minority Decision in Online-Barnga. HCI (5) 2021: 269-285 - [c157]Naoya Matsuda, Iko Nakari, Ryotaro Arai, Hiroyuki Sato, Keiki Takadama, Masanori Hirose, Hiroshi Hasegawa, Makoto Shiraishi, Takahide Matsuda:
Alzheimer Dementia Detection based on Circadian Rhythm Disorder of Heartrate. LifeTech 2021: 360-364 - [i2]Fumito Uwano, Keiki Takadama:
Directionality Reinforcement Learning to Operate Multi-Agent System without Communication. CoRR abs/2110.05773 (2021) - 2020
- [j60]Sotetsu Suzugamine, Takeru Aoki, Keiki Takadama, Hiroyuki Sato:
Self-Structured Cortical Learning Algorithm by Dynamically Adjusting Columns and Cells. J. Adv. Comput. Intell. Intell. Informatics 24(2): 185-198 (2020) - [j59]Fumito Uwano, Keiki Takadama:
Reward Value-Based Goal Selection for Agents' Cooperative Route Learning Without Communication in Reward and Goal Dynamism. SN Comput. Sci. 1(3): 182 (2020) - [j58]Tomohiro Harada, Keiki Takadama:
Analysis of semi-asynchronous multi-objective evolutionary algorithm with different asynchronies. Soft Comput. 24(4): 2917-2939 (2020) - [c156]Masakazu Tadokoro, Satoshi Hasegawa, Takato Tatsumi, Hiroyuki Sato, Keiki Takadama:
Local Covering: Adaptive Rule Generation Method Using Existing Rules for XCS. CEC 2020: 1-8 - [c155]Tomoaki Takagi, Keiki Takadama, Hiroyuki Sato:
Non-dominated Solution Sampling Using Environmental Selection in EMO algorithms. CEC 2020: 1-9 - [c154]Kensuke Kano, Tomoaki Takagi, Keiki Takadama, Hiroyuki Sato:
Preliminary study of adaptive grid-based decomposition on many-objective evolutionary optimization. GECCO Companion 2020: 1373-1380 - [c153]Tomoaki Takagi, Keiki Takadama, Hiroyuki Sato:
Incremental lattice design of weight vector set. GECCO Companion 2020: 1486-1494 - [c152]Kohei Yamamoto, Tomoaki Takagi, Keiki Takadama, Hiroyuki Sato:
Visual mapping of multi-objective optimization problems and evolutionary algorithms. GECCO Companion 2020: 1872-1879 - [c151]Yoshimiki Maekawa, Fumito Uwano, Eiki Kitajima, Keiki Takadama:
How to Emote for Consensus Building in Virtual Communication. HCI (5) 2020: 194-205 - [c150]Shio Kawakami, Tomoaki Takagi, Keiki Takadama, Hiroyuki Sato:
Distance Minimization Problems for Multi-factorial Evolutionary Optimization Benchmarking. HIS 2020: 710-719 - [c149]Iko Nakari, Eiki Kitajima, Yusuke Tajima, Keiki Takadama:
Non-contact Sleep Apnea Syndrome Detection Based on What Random Forests Learned. LifeTech 2020: 240-244 - [c148]Takeru Aoki, Keiki Takadama, Hiroyuki Sato:
Column-based Decoder of Internal Prediction Representation in Cortical Learning Algorithms. SCIS/ISIS 2020: 1-7 - [c147]Yukiko Fukumoto, Masakazu Tadokoro, Keiki Takadama:
Cooperative Multi-agent Inverse Reinforcement Learning Based on Selfish Expert and its Behavior Archives. SSCI 2020: 2202-2209 - [i1]Yohei Hayamizu, Saeid Amiri, Kishan Chandan, Shiqi Zhang, Keiki Takadama:
Guided Dyna-Q for Mobile Robot Exploration and Navigation. CoRR abs/2004.11456 (2020)
2010 – 2019
- 2019
- [j57]Ioana Baldini, Clark W. Barrett, Antonio Chella, Carlos Cinelli, David Gamez, Leilani H. Gilpin, Knut Hinkelmann, Dylan Holmes, Takashi Kido, Murat Kocaoglu, William F. Lawless, Alessio Lomuscio, Jamie C. Macbeth, Andreas Martin, Ranjeev Mittu, Evan Patterson, Donald Sofge, Prasad Tadepalli, Keiki Takadama, Shomir Wilson:
Reports of the AAAI 2019 Spring Symposium Series. AI Mag. 40(3): 59-66 (2019) - [c146]Takashi Kido, Keiki Takadama:
The Challenges for Interpretable AI for Well-being. AAAI Spring Symposium: Interpretable AI for Well-being 2019 - [c145]Iko Nakari, Yusuke Tajima, Akari Tobaru, Keiki Takadama:
WAKE Detection During Sleep using Random Forest for Apnea Syndrome Patients. AAAI Spring Symposium: Interpretable AI for Well-being 2019 - [c144]Keiki Takadama:
What Makes It Difficult To Apply AI Into Well-being and Its Solution: An Example of Sleep Apnea Syndrome. AAAI Spring Symposium: Interpretable AI for Well-being 2019 - [c143]Ryo Takano, Sho Kajihara, Satoshi Hasegawa, Eiki Kitajima, Keiki Takadama, Toru Shimuta, Toru Yabe, Hideo Matsumoto:
Toward Good Circadian Rhythm through an valuate of Stress Condition. AAAI Spring Symposium: Interpretable AI for Well-being 2019 - [c142]Ryo Takano, Akari Tobaru, Iko Nakari, Keiki Takadama:
Sleep Stage Estimation Through Mattress Sensor. AAAI Spring Symposium: Interpretable AI for Well-being 2019 - [c141]Akari Tobaru, Yusuke Tajima, Keiki Takadama:
Sleep Stage Estimation using Heart Rate Variability divided by Sleep Cycle with Relative Evaluation. AAAI Spring Symposium: Interpretable AI for Well-being 2019 - [c140]Tomoaki Takagi, Keiki Takadama, Hiroyuki Sato:
A Distribution Control of Weight Vector Set for Multi-objective Evolutionary Algorithms. BICT 2019: 70-80 - [c139]Takuya Iwase, Ryo Takano, Fumito Uwano, Hiroyuki Sato, Keiki Takadama:
Niche Radius Adaptation in Bat Algorithm for Locating Multiple Optima in Multimodal Functions. CEC 2019: 800-807 - [c138]Keiki Takadama, Daichi Yamazaki, Masaya Nakata, Hiroyuki Sato:
Complex-Valued-based Learning Classifier System for POMDP Environments. CEC 2019: 1852-1859 - [c137]Takato Tatsumi, Keiki Takadama:
Comparison of Statistical Table- and Non-Statistical Table-based XCS in Noisy Environments. CEC 2019: 1875-1882 - [c136]Masakazu Tadokoro, Satoshi Hasegawa, Takato Tatsumi, Hiroyuki Sato, Keiki Takadama:
Knowledge Extraction from XCSR Based on Dimensionality Reduction and Deep Generative Models. CEC 2019: 1883-1890 - [c135]Keiki Takadama, Keiji Sato, Hiroyuki Sato:
Evolving Generalized Solutions for Robust Multi-objective Optimization: Transportation Analysis in Disaster. EMO 2019: 491-503 - [c134]Takato Tatsumi, Keiki Takadama:
XCS-CR for handling input, output, and reward noise. GECCO (Companion) 2019: 1303-1311 - [c133]Tomohiro Yamaguchi, Shota Nagahama, Yoshihiro Ichikawa, Keiki Takadama:
Model-Based Multi-objective Reinforcement Learning with Unknown Weights. HCI (5) 2019: 311-321 - [c132]Yoshimiki Maekawa, Fumito Uwano, Eiki Kitajima, Keiki Takadama:
How to Design Adaptable Agents to Obtain a Consensus with Omoiyari. HCI (4) 2019: 462-475 - [c131]Ryota Kobayashi, Ryo Takano, Hiroyuki Sato, Keiki Takadama:
Simultaneous Local Adaptation for Different Local Properties. IES 2019: 216-227 - [c130]Takahiro Majima, Keiki Takadama, Daisuke Watanabe, Taro Aratani, Keiji Sato:
Application of Multi Agent System and Transition Matrix Analysis to Logistics System for Equal Distribution under Disaster Situation. SICE 2019: 108-114 - [c129]Iko Nakari, Akinori Murata, Eiki Kitajima, Hiroyuki Sato, Keiki Takadama:
Sleep Apnea Syndrome Detection based on Biological Vibration Data from Mattress Sensor. SSCI 2019: 550-556 - [e8]Takashi Kido, Keiki Takadama:
Proceedings of the Symposium Interpretable AI for Well-being: Understanding Cognitive Bias and Social Embeddedness co-located with Association for the Advancement of Artificial Intelligence 2019 Spring Symposium (AAAI-Spring Symposium 2019), Stanford, CA, March 25-27, 2019. CEUR Workshop Proceedings 2448, CEUR-WS.org 2019 [contents] - 2018
- [j56]Christopher Amato, Haitham Bou-Ammar, Elizabeth F. Churchill, Erez Karpas, Takashi Kido, Mike Kuniavsky, William F. Lawless, Francesca Rossi, Frans A. Oliehoek, Stephen Russell, Keiki Takadama, Siddharth Srivastava, Karl Tuyls, Philip van Allen, Kristen Brent Venable, Peter Vrancx, Shiqi Zhang:
Reports on the 2018 AAAI Spring Symposium Series. AI Mag. 39(4): 29-35 (2018) - [j55]Takahiro Majima, Keiki Takadama, Daisuke Watanabe, Taro Aratani, Keiji Sato:
Transportation simulator for disaster circumstance and bottleneck analysis. Artif. Life Robotics 23(4): 593-599 (2018) - [c128]Takashi Kido, Keiki Takadama:
The Challenges for Understanding Cognitive Bias and Humanity for Well-Being AI - Beyond Machine Intelligence. AAAI Spring Symposia 2018 - [c127]Yusuke Tajima, Akinori Murata, Tomohiro Harada, Keiki Takadama:
Sleep Stage Re-Estimation Method According To Sleep Cycle Change. AAAI Spring Symposia 2018 - [c126]Keiki Takadama:
Can Machine Learning Correct Commonly Accepted Knowledge and Provide Understandable Knowledge in Care Support Domain? Tackling Cognitive Bias and Humanity from Machine Learning Perspective. AAAI Spring Symposia 2018 - [c125]Ryo Takano, Satoshi Hasegawa, Yuta Umenai, Takato Tatsumi, Keiki Takadama, Toru Shimuta, Toru Yabe, Hideo Matsumoto:
Study of Analytical Methods on the Relationship between Sleep Quality and Stress with a focus on Human Circadian Rhythm. AAAI Spring Symposia 2018 - [c124]Akari Tobaru, Fumito Uwano, Takuya Iwase, Kazuma Matsumoto, Ryo Takano, Yusuke Tajima, Yuta Umenai, Keiki Takadama:
Improving Sleep Stage Estimation Accuracy by Circadian Rhythm Extracted from a Low Frequency Component of Heart Rate. AAAI Spring Symposia 2018 - [c123]Fumito Uwano, Keiki Takadama:
Ensemble Heart Rate Extraction Method for Biological Data from Water Pressure Sensor. AAAI Spring Symposia 2018 - [c122]Ryo Takano, Hiroyuki Sato, Keiki Takadama:
Artificial bee colony algorithm based on adaptive local information sharing: approach for several dynamic changes. GECCO (Companion) 2018: 95-96 - [c121]Yuta Umenai, Fumito Uwano, Hiroyuki Sato, Keiki Takadama:
Multiple swarm intelligence methods based on multiple population with sharing best solution for drastic environmental change. GECCO (Companion) 2018: 97-98 - [c120]Kazuma Matsumoto, Ryo Takano, Takato Tatsumi, Hiroyuki Sato, Tim Kovacs, Keiki Takadama:
XCSR based on compressed input by deep neural network for high dimensional data. GECCO (Companion) 2018: 1418-1425 - [c119]Takato Tatsumi, Tim Kovacs, Keiki Takadama:
XCS-CR: determining accuracy of classifier by its collective reward in action set toward environment with action noise. GECCO (Companion) 2018: 1457-1464 - [c118]Fumito Uwano, Koji Dobashi, Keiki Takadama, Tim Kovacs:
Generalizing rules by random forest-based learning classifier systems for high-dimensional data mining. GECCO (Companion) 2018: 1465-1472 - [c117]Caili Zhang, Takato Tatsumi, Hiyoyuki Sato, Tim Kovacs, Keiki Takadama:
Classifier generalization for comprehensive classifiers subsumption in XCS. GECCO (Companion) 2018: 1854-1861 - [c116]Takato Okudo, Tomohiro Yamaguchi, Keiki Takadama:
Generating Learning Environments Derived from Found Solutions by Adding Sub-goals Toward the Creative Learning Support. HCI (5) 2018: 313-330 - [c115]Eiki Kitajima, Caili Zhang, Haruyuki Ishii, Fumito Uwano, Keiki Takadama:
Correcting Wrongly Determined Opinions of Agents in Opinion Sharing Model. HCI (4) 2018: 658-676 - [c114]Fumito Uwano, Keiki Takadama:
Strategy for Learning Cooperative Behavior with Local Information for Multi-agent Systems. PRIMA 2018: 663-670 - [c113]Sotetsu Suzugamine, Takeru Aoki, Keiki Takadama, Hiroyuki Sato:
A Study on a Cortical Learning Algorithm Dynamically Adjusting Columns and Cells. SCIS&ISIS 2018: 267-274 - [c112]Takato Tatsumi, Keiki Takadama:
XCS for Missing Attributes in Data. SCIS&ISIS 2018: 329-334 - [e7]Hernán E. Aguirre, Keiki Takadama:
Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2018, Kyoto, Japan, July 15-19, 2018. ACM 2018 [contents] - [e6]Hernán E. Aguirre, Keiki Takadama:
Proceedings of the Genetic and Evolutionary Computation Conference Companion, GECCO 2018, Kyoto, Japan, July 15-19, 2018. ACM 2018 [contents] - 2017
- [j54]Jeannette Bohg, Xavier Boix, Nancy Chang, Elizabeth F. Churchill, Vivian Chu, Fei Fang, Jerome Feldman, Avelino J. Gonzalez, Takashi Kido, William F. Lawless, José L. Montaña, Santiago Ontañón, Jivko Sinapov, Donald A. Sofge, Luc Steels, Molly Wright Steenson, Keiki Takadama, Amulya Yadav:
Reports on the 2017 AAAI Spring Symposium Series. AI Mag. 38(4): 99-106 (2017) - [j53]Keiki Takadama, Kazuteru Miyazaki:
Editorial: Cutting Edge of Reinforcement Learning and its Hybrid Methods. J. Adv. Comput. Intell. Intell. Informatics 21(5): 833 (2017) - [j52]Kazuma Matsumoto, Takato Tatsumi, Hiroyuki Sato, Tim Kovacs, Keiki Takadama:
XCSR Learning from Compressed Data Acquired by Deep Neural Network. J. Adv. Comput. Intell. Intell. Informatics 21(5): 856-867 (2017) - [j51]Hiroyasu Matsushima, Keiki Takadama:
Exemplar-Based Learning Classifier System with Dynamic Matching Range for Imbalanced Data. J. Adv. Comput. Intell. Intell. Informatics 21(5): 868-875 (2017) - [j50]Caili Zhang, Takato Tatsumi, Masaya Nakata, Keiki Takadama:
Approach to Clustering with Variance-Based XCS. J. Adv. Comput. Intell. Intell. Informatics 21(5): 885-894 (2017) - [j49]Takato Tatsumi, Hiroyuki Sato, Keiki Takadama:
Learning Classifier System Based on Mean of Reward. J. Adv. Comput. Intell. Intell. Informatics 21(5): 895-906 (2017) - [j48]Takato Okudo, Tomohiro Yamaguchi, Akinori Murata, Takato Tatsumi, Fumito Uwano, Keiki Takadama:
Supporting the Exploration of the Learning Goals for a Continuous Learner Toward Creative Learning. J. Adv. Comput. Intell. Intell. Informatics 21(5): 907-916 (2017) - [j47]Fumito Uwano, Keiki Takadama:
Comparison Between Reinforcement Learning Methods with Different Goal Selections in Multi-Agent Cooperation. J. Adv. Comput. Intell. Intell. Informatics 21(5): 917-929 (2017) - [j46]Tomohiro Harada, Keiki Takadama:
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) - [j45]Fumito Uwano, Yusuke Tajima, Akinori Murata, Keiki Takadama:
Recovery System Based on Exploration-Biased Genetic Algorithm for Stuck Rover in Planetary Exploration. J. Robotics Mechatronics 29(5): 877-886 (2017) - [c111]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 - [c110]Masafumi Ishii, Jinhwan Kwon, Keiki Takadama, Maki Sakamoto:
Visual Impression Generation System Based on Boids Algorithm. AAAI Spring Symposia 2017 - [c109]Takashi Kido, Keiki Takadama:
Wellbeing AI Invited Speaker Abstracts. AAAI Spring Symposia 2017 - [c108]Yusuke Tajima, Tomohiro Harada, Keiki Takadama:
Sleep Stage Estimation Based on Appriximate Heartrate Calculated from Other Persons. AAAI Spring Symposia 2017 - [c107]Keiki Takadama:
Towards Guideline for Applying Machine Learning into Care Support Systems. AAAI Spring Symposia 2017 - [c106]Tomohiro Harada, Keiki Takadama:
Performance comparison of parallel asynchronous multi-objective evolutionary algorithm with different asynchrony. CEC 2017: 1215-1222 - [c105]Takato Tatsumi, Hiroyuki Sato, Tim Kovacs, Keiki Takadama:
Applying variance-based Learning Classifier System without Convergence of Reward Estimation into various Reward distribution. CEC 2017: 2630-2637 - [c104]Hiroyuki Sato, Minami Miyakawa, Keiki Takadama:
An improved MOEA/D utilizing variation angles for multi-objective optimization. GECCO (Companion) 2017: 163-164 - [c103]Masaya Nakata, Will N. Browne, Tomoki Hamagami, Keiki Takadama:
Theoretical XCS parameter settings of learning accurate classifiers. GECCO 2017: 473-480 - [c102]Takato Tatsumi, Hiroyuki Sato, Keiki Takadama:
Automatic adjustment of selection pressure based on range of reward in learning classifier system. GECCO 2017: 505-512 - [c101]Tomohiro Harada, Keiki Takadama:
A study of self-adaptive semi-asynchronous evolutionary algorithm on multi-objective optimization problem. GECCO (Companion) 2017: 1812-1819 - [c100]Takato Okudo, Keiki Takadama, Tomohiro Yamaguchi:
Designing the Learning Goal Space for Human Toward Acquiring a Creative Learning Skill. HCI (4) 2017: 62-73 - [c99]Akinori Murata, Hiroyuki Sato, Keiki Takadama:
Towards Adaptive Aircraft Landing Order with Aircraft Routes Partially Fixed by Air Traffic Controllers as Human Intervention. HCI (4) 2017: 422-433 - [c98]Motoaki Kakuguchi, Minami Miyakawa, Keiki Takadama, Hiroyuki Sato:
Multi-objetive optimization problem mapping based on algorithmic parameter rankings. SSCI 2017: 1-8 - [c97]Yuta Umenai, Fumito Uwano, Hiroyuki Sato, Keiki Takadama:
Strategies to Improve Cuckoo Search Toward Adapting Randomly Changing Environment. ICSI (1) 2017: 573-582 - 2016
- [j44]Christopher Amato, Ofra Amir, Joanna Bryson, Barbara J. Grosz, Bipin Indurkhya, Emre Kiciman, Takashi Kido, William F. Lawless, Miao Liu, Braden McDorman, Ross Mead, Frans A. Oliehoek, Andrew Specian, Georgi Stojanov, Keiki Takadama:
Reports of the AAAI 2016 Spring Symposium Series. AI Mag. 37(4): 83-88 (2016) - [j43]Kiyohiko Hattori, Naoki Tatebe, Toshinori Kagawa, Yasunori Owada, Lin Shan, Katsuhiro Temma, Kiyoshi Hamaguchi, Keiki Takadama:
Deployment of wireless mesh network using RSSI-based swarm robots. Artif. Life Robotics 21(4): 434-442 (2016) - [j42]Minami Miyakawa, Keiki Takadama, Hiroyuki Sato:
Controlling selection areas of useful infeasible solutions for directed mating in evolutionary constrained multi-objective optimization. Ann. Math. Artif. Intell. 76(1-2): 25-46 (2016) - [j41]Fumito Uwano, Naoki Tatebe, Masaya Nakata, Keiki Takadama, Tim Kovacs:
Reinforcement Learning with Internal Reward for Multi-Agent Cooperation: A Theoretical Approach. EAI Endorsed Trans. Collab. Comput. 2(8): e2 (2016) - [j40]Tomohiro Yamaguchi, Takuma Nishimura, Keiki Takadama:
Awareness Based Recommendation: Passively Interactive Learning System. Int. J. Robotics Appl. Technol. 4(1): 83-99 (2016) - [j39]Takahiro Majima, Keiki Takadama, Daisuke Watanabe, Mitujiro Katuhara:
Characteristic and application of network evolution model for public transport network. Multiagent Grid Syst. 12(1): 1-11 (2016) - [j38]Akinori Murata, Masaya Nakata, Hiroyuki Sato, Tim Kovacs, Keiki Takadama:
Optimization of Aircraft Landing Route and Order: An approach of Hierarchical Evolutionary Computation. EAI Endorsed Trans. Self Adapt. Syst. 2(6): e5 (2016) - [c96]