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2020 – today
- 2024
[j26]Shintaro Ueki, Fujio Toriumi, Toshiharu Sugawara:
Game-theoretic implications for uncovering the effects of virtual tipping in complex user networks. Appl. Netw. Sci. 9(1): 44 (2024)- [j25]Yidong Bai
, Toshiharu Sugawara:
Locally Centralized Execution for Less Redundant Computation in Multi-Agent Cooperation. Inf. 15(5): 279 (2024) - [j24]Yoshie Suzuki, Stephen Raharja, Toshiharu Sugawara:
Fair Path Generation for Multiple Agents Using Ant Colony Optimization in Consecutive Pattern Formations. J. Adv. Comput. Intell. Intell. Informatics 28(1): 159-168 (2024) - [c153]Yuki Miyashita, Toshiharu Sugawara:
Scheduling and Negotiation Method for Double Synchronized Multi-Agent Pickup and Delivery Problem. ICAART (1) 2024: 321-332 - [i8]Yidong Bai, Toshiharu Sugawara:
Reducing Redundant Computation in Multi-Agent Coordination through Locally Centralized Execution. CoRR abs/2404.13096 (2024) - 2023
- [j23]Yutaro Usui, Fujio Toriumi, Toshiharu Sugawara:
User behaviors in consumer-generated media under monetary reward schemes. J. Comput. Soc. Sci. 6(1): 389-409 (2023) - [j22]Tomoki Yamauchi, Yuki Miyashita, Toshiharu Sugawara:
Efficient Path and Action Planning Method for Multi-Agent Pickup and Delivery Tasks under Environmental Constraints. SN Comput. Sci. 4(1): 83 (2023) - [c152]Shintaro Ueki, Fujio Toriumi, Toshiharu Sugawara:
User's Position-Dependent Strategies in Consumer-Generated Media with Monetary Rewards. ASONAM 2023: 325-329 - [c151]Yuki Miyashita, Tomoki Yamauchi, Toshiharu Sugawara:
Distributed Planning with Asynchronous Execution with Local Navigation for Multi-agent Pickup and Delivery Problem. AAMAS 2023: 914-922 - [c150]Gentoku Nakasone, Toshiharu Sugawara:
Interpretation Using Classified Gradient-Based Saliency Maps for Two-Player Board Games. CoG 2023: 1-8 - [c149]Shintaro Ueki, Fujio Toriumi, Toshiharu Sugawara:
Influence of Virtual Tipping and Collection Rate in Social Live Streaming Services. COMPLEX NETWORKS (4) 2023: 116-128 - [c148]Junjie Zhong, Toshiharu Sugawara:
Modeling Others as a Player in Non-cooperative Game for Multi-agent Coordination. EANN 2023: 520-531 - [c147]Yidong Bai, Toshiharu Sugawara:
Learning to Communicate Using Action Probabilities for Multi-Agent Cooperation. ICA 2023: 31-36 - [c146]Kohei Matsumoto, Keisuke Yoneda, Toshiharu Sugawara:
Autonomous Energy-Saving Behaviors with Fulfilling Requirements for Multi-Agent Cooperative Patrolling Problem. ICAART (1) 2023: 37-47 - [c145]Yoshinari Motokawa, Toshiharu Sugawara:
Interpretability for Conditional Coordinated Behavior in Multi-Agent Reinforcement Learning. IJCNN 2023: 1-8 - [c144]Yoshinari Motokawa, Toshiharu Sugawara:
Strategy-Following Multi-Agent Deep Reinforcement Learning through External High-Level Instruction. KES 2023: 2798-2807 - [i7]Yuki Miyashita, Tomoki Yamauchi, Toshiharu Sugawara:
Distributed Planning with Asynchronous Execution with Local Navigation for Multi-agent Pickup and Delivery Problem. CoRR abs/2302.09250 (2023) - [i6]Yoshinari Motokawa, Toshiharu Sugawara:
Interpretability for Conditional Coordinated Behavior in Multi-Agent Reinforcement Learning. CoRR abs/2304.10375 (2023) - [i5]Shintaro Ueki, Fujio Toriumi, Toshiharu Sugawara:
Effect of Monetary Reward on Users' Individual Strategies Using Co-Evolutionary Learning. CoRR abs/2306.00492 (2023) - [i4]Shintaro Ueki, Fujio Toriumi, Toshiharu Sugawara:
User's Position-Dependent Strategies in Consumer-Generated Media with Monetary Rewards. CoRR abs/2310.04805 (2023) - 2022
- [j21]Yuki Miyashita, Toshiharu Sugawara:
Two-stage reward allocation with decay for multi-agent coordinated behavior for sequential cooperative task by using deep reinforcement learning. Auton. Intell. Syst. 2(1): 1-18 (2022) - [c143]Tomoki Yamauchi, Yuki Miyashita, Toshiharu Sugawara:
Standby-Based Deadlock Avoidance Method for Multi-Agent Pickup and Delivery Tasks. AAMAS 2022: 1427-1435 - [c142]Yuki Miyashita, Tomoki Yamauchi, Toshiharu Sugawara:
Distributed and Asynchronous Planning and Execution for Multi-agent Systems through Short-Sighted Conflict Resolution. COMPSAC 2022: 14-23 - [c141]Sota Tsuiki, Keisuke Yoneda, Toshiharu Sugawara:
Negotiation Protocol with Learned Handover of Important Tasks for Planned Suspensions in Multi-agent Patrol Problems. ICAART (Revised Selected Paper 2022: 27-47 - [c140]Sota Tsuiki, Keisuke Yoneda, Toshiharu Sugawara:
Task Handover Negotiation Protocol for Planned Suspension based on Estimated Chances of Negotiations in Multi-agent Patrolling. ICAART (1) 2022: 83-93 - [c139]Yuki Miyashita, Toshiharu Sugawara:
Flexible Exploration Strategies in Multi-Agent Reinforcement Learning for Instability by Mutual Learning. ICMLA 2022: 579-584 - [c138]Yidong Bai, Toshiharu Sugawara:
Imbalanced Equilibrium: Emergence of Social Asymmetric Coordinated Behavior in Multi-agent Games. ICONIP (2) 2022: 305-316 - [c137]Stephen Raharja, Toshiharu Sugawara:
Identifying Top-k Peaks Using an Extended Particle Swarm Optimization Algorithm with Re-diversification Mechanism. IIAI-AAI 2022: 359-366 - [c136]Yoshinari Motokawa, Toshiharu Sugawara:
Distributed Multi-Agent Deep Reinforcement Learning for Robust Coordination against Noise. IJCNN 2022: 1-8 - [c135]Yukita Fujitani, Tomoki Yamauchi, Yuki Miyashita, Toshiharu Sugawara:
Deadlock-Free Method for Multi-Agent Pickup and Delivery Problem Using Priority Inheritance with Temporary Priority. KES 2022: 1552-1561 - [c134]Yoshihiro Oguni, Yuki Miyashita, Toshiharu Sugawara:
Shifting Reward Assignment for Learning Coordinated Behavior in Time-Limited Ordered Tasks. PAAMS 2022: 294-306 - [c133]Tomoki Yamauchi, Yuki Miyashita, Toshiharu Sugawara:
Task Selection Algorithm for Multi-Agent Pickup and Delivery with Time Synchronization. PRIMA 2022: 458-474 - [c132]Yoshie Suzuki, Stephen Raharja, Toshiharu Sugawara:
Fair Formation Control of Multiple Agents Using Ant Colony Optimization. SCIS/ISIS 2022: 1-6 - [i3]Tomoki Yamauchi, Yuki Miyashita, Toshiharu Sugawara:
Standby-Based Deadlock Avoidance Method for Multi-Agent Pickup and Delivery Tasks. CoRR abs/2201.06014 (2022) - [i2]Yoshinari Motokawa, Toshiharu Sugawara:
Distributed Multi-Agent Deep Reinforcement Learning for Robust Coordination against Noise. CoRR abs/2205.09705 (2022) - [i1]Yukita Fujitani, Tomoki Yamauchi, Yuki Miyashita, Toshiharu Sugawara:
Deadlock-Free Method for Multi-Agent Pickup and Delivery Problem Using Priority Inheritance with Temporary Priority. CoRR abs/2205.12504 (2022) - 2021
- [j20]Yuki Miyashita, Toshiharu Sugawara:
Analysis of coordinated behavior structures with multi-agent deep reinforcement learning. Appl. Intell. 51(2): 1069-1085 (2021) - [c131]Yutaro Usui, Fujio Toriumi, Toshiharu Sugawara:
Impact of Monetary Rewards on Users' Behavior in Social Media. COMPLEX NETWORKS 2021: 632-643 - [c130]Tomoki Yamauchi, Yuki Miyashita, Toshiharu Sugawara:
Path and Action Planning in Non-uniform Environments for Multi-agent Pickup and Delivery Tasks. EUMAS 2021: 37-54 - [c129]Sota Tsuiki, Keisuke Yoneda, Toshiharu Sugawara:
Reducing Efficiency Degradation Due to Scheduled Agent Suspensions by Task Handover in Multi-Agent Cooperative Patrol Problems. FLAIRS 2021 - [c128]Naoki Yoshida, Itsuki Noda, Toshiharu Sugawara:
Distributed Service Area Control for Ride Sharing by using Multi-Agent Deep Reinforcement Learning. ICAART (1) 2021: 101-112 - [c127]Katsuya Hattori, Toshiharu Sugawara:
Effective Area Partitioning in a Multi-Agent Patrolling Domain for Better Efficiency. ICAART (1) 2021: 281-288 - [c126]Yoshinari Motokawa, Toshiharu Sugawara:
MAT-DQN: Toward Interpretable Multi-agent Deep Reinforcement Learning for Coordinated Activities. ICANN (4) 2021: 556-567 - [c125]Koki Sato, Toshiharu Sugawara:
Multi-Agent Task Allocation Based on Reciprocal Trust in Distributed Environments. KES-AMSTA 2021: 477-488 - 2020
- [j19]Elhadji Amadou Oury Diallo, Ayumi Sugiyama, Toshiharu Sugawara:
Coordinated behavior of cooperative agents using deep reinforcement learning. Neurocomputing 396: 230-240 (2020) - [c124]Elhadji Amadou Oury Diallo, Toshiharu Sugawara:
Multi-Agent Pattern Formation with Deep Reinforcement Learning (Student Abstract). AAAI 2020: 13779-13780 - [c123]Yizhou Yan, Fujio Toriumi, Toshiharu Sugawara:
Influence of Retweeting on the Behaviors of Social Networking Service Users. COMPLEX NETWORKS (1) 2020: 671-682 - [c122]Zean Zhu, Elhadji Amadou Oury Diallo, Toshiharu Sugawara:
Learning Efficient Coordination Strategy for Multi-step Tasks in Multi-agent Systems using Deep Reinforcement Learning. ICAART (1) 2020: 287-294 - [c121]Yuki Miyashita, Toshiharu Sugawara:
Coordinated Behavior for Sequential Cooperative Task Using Two-Stage Reward Assignment with Decay. ICONIP (2) 2020: 257-269 - [c120]Elhadji Amadou Oury Diallo, Toshiharu Sugawara:
Multi-Agent Pattern Formation: a Distributed Model-Free Deep Reinforcement Learning Approach. IJCNN 2020: 1-8 - [c119]Xiaohui Zhu, Toshiharu Sugawara:
Meta-Reward Model Based on Trajectory Data with k-Nearest Neighbors Method. IJCNN 2020: 1-8 - [c118]Yuka Ishihara, Toshiharu Sugawara:
Multi-Agent Task Allocation Based on the Learning of Managers and Local Preference Selections. KES 2020: 675-684 - [c117]Naoki Yoshida, Itsuki Noda, Toshiharu Sugawara:
Multi-agent Service Area Adaptation for Ride-Sharing Using Deep Reinforcement Learning. PAAMS 2020: 363-375 - [c116]Jiahao Peng, Toshiharu Sugawara:
Policy Advisory Module for Exploration Hindrance Problem in Multi-agent Deep Reinforcement Learning. PRIMA 2020: 133-149 - [c115]Ken Smith, Yuki Miyashita, Toshiharu Sugawara:
Analysis of Coordination Structures of Partially Observing Cooperative Agents by Multi-agent Deep Q-Learning. PRIMA 2020: 150-164
2010 – 2019
- 2019
- [j18]Ayumi Sugiyama, Vourchteang Sea, Toshiharu Sugawara:
Emergence of divisional cooperation with negotiation and re-learning and evaluation of flexibility in continuous cooperative patrol problem. Knowl. Inf. Syst. 60(3): 1587-1609 (2019) - [c114]Yuki Miyashita, Toshiharu Sugawara:
Coordination Structures Generated by Deep Reinforcement Learning in Distributed Task Executions. AAMAS 2019: 2129-2131 - [c113]Yutaro Miura, Fujio Toriumi, Toshiharu Sugawara:
Analysis of Diversity and Dynamics in Co-evolution of Cooperation in Social Networking Services. COMPLEX NETWORKS (1) 2019: 495-506 - [c112]Sonoko Kimura, Kimitaka Asatani, Toshiharu Sugawara:
Comparison of Opinion Polarization on Single-Layer and Multiplex Networks. COMPLEX NETWORKS (2) 2019: 709-721 - [c111]Yutaro Miura, Fujio Toriumi, Toshiharu Sugawara:
Multiple world genetic algorithm to analyze individually advantageous behaviors in complex networks. GECCO (Companion) 2019: 297-298 - [c110]Ayumi Sugiyama, Lingying Wu, Toshiharu Sugawara:
Learning of Activity Cycle Length based on Battery Limitation in Multi-agent Continuous Cooperative Patrol Problems. ICAART (1) 2019: 62-71 - [c109]Ayumi Sugiyama, Lingying Wu, Toshiharu Sugawara:
Improvement of Multi-agent Continuous Cooperative Patrolling with Learning of Activity Length. ICAART (Revised Selected Papers) 2019: 270-292 - [c108]Yuki Miyashita, Toshiharu Sugawara:
Cooperation and Coordination Regimes by Deep Q-Learning in Multi-agent Task Executions. ICANN (1) 2019: 541-554 - [c107]Elhadji Amadou Oury Diallo, Toshiharu Sugawara:
Coordination in Adversarial Multi-Agent with Deep Reinforcement Learning Under Partial Observability. ICTAI 2019: 198-205 - [c106]Tomoki Yamauchi, Rina Ide, Toshiharu Sugawara:
Fair and Effective Elevator Car Dispatching Method in Elevator Group Control System using Cameras. KES 2019: 455-464 - [c105]Lingying Wu, Ayumi Sugiyama, Toshiharu Sugawara:
Energy-Efficient Strategies for Multi-Agent Continuous Cooperative Patrolling Problems. KES 2019: 465-474 - [c104]Yuki Miyashita, Toshiharu Sugawara:
Coordination in Collaborative Work by Deep Reinforcement Learning with Various State Descriptions. PRIMA 2019: 550-558 - [c103]Lingying Wu, Toshiharu Sugawara:
Strategies for Energy-Aware Multi-agent Continuous Cooperative Patrolling Problems Subject to Requirements. PRIMA 2019: 585-593 - [c102]Yutaro Miura, Fujio Toriumi, Toshiharu Sugawara:
Multiple-World Genetic Algorithm to Identify Locally Reasonable Behaviors in Complex Social Networks. SMC 2019: 3665-3672 - 2018
- [c101]Vourchteang Sea, Ayumi Sugiyama, Toshiharu Sugawara:
Frequency-Based Multi-agent Patrolling Model and Its Area Partitioning Solution Method for Balanced Workload. CPAIOR 2018: 530-545 - [c100]Ryoya Funato, Toshiharu Sugawara:
Efficient Task Allocation with Communication Delay Based on Reciprocal Teams. ICA 2018: 50-54 - [c99]Elhadji Amadou Oury Diallo, Toshiharu Sugawara:
Learning Strategic Group Formation for Coordinated Behavior in Adversarial Multi-Agent with Double DQN. PRIMA 2018: 458-466 - [c98]Yutaro Miura, Fujio Toriumi, Toshiharu Sugawara:
Evolutionary Learning Model of Social Networking Services with Diminishing Marginal Utility. WWW (Companion Volume) 2018: 1323-1329 - 2017
- [j17]Vourchteang Sea, Chihiro Kato, Toshiharu Sugawara:
Coordinated Area Partitioning Method by Autonomous Agents for Continuous Cooperative Tasks. J. Inf. Process. 25: 75-87 (2017) - [c97]Tomoaki Otsuka, Toshiharu Sugawara:
Promotion of Robust Cooperation Among Agents in Complex Networks by Enhanced Expectation-of-Cooperation Strategy. COMPLEX NETWORKS 2017: 815-828 - [c96]Masashi Hayano, Naoki Iijima, Toshiharu Sugawara:
Asynchronous Agent Teams for Collaborative Tasks Based on Bottom-Up Alliance Formation and Adaptive Behavioral Strategies. DASC/PiCom/DataCom/CyberSciTech 2017: 589-596 - [c95]Elhadji Amadou Oury Diallo, Ayumi Sugiyama, Toshiharu Sugawara:
Learning to Coordinate with Deep Reinforcement Learning in Doubles Pong Game. ICMLA 2017: 14-19 - [c94]Naoki Iijima, Ayumi Sugiyama, Masashi Hayano, Toshiharu Sugawara:
Adaptive Task Allocation Based on Social Utility and Individual Preference in Distributed Environments. KES 2017: 91-98 - [c93]Ayumi Sugiyama, Toshiharu Sugawara:
Improvement of Robustness to Environmental Changes by Autonomous Divisional Cooperation in Multi-agent Cooperative Patrol Problem. PAAMS 2017: 259-271 - [c92]Tomoaki Otsuka, Toshiharu Sugawara:
Robust spread of cooperation by expectation-of-cooperation strategy with simple labeling method. WI 2017: 483-490 - 2016
- [j16]Yuki Hirahara, Fujio Toriumi, Toshiharu Sugawara:
Cooperation-dominant Situations in SNS-norms Game on Complex and Facebook Networks. New Gener. Comput. 34(3): 273-290 (2016) - [c91]Ryosuke Shibusawa, Tomoaki Otsuka, Toshiharu Sugawara:
Emergence of Cooperation in Complex Agent Networks Based on Expectation of Cooperation: (Extended Abstract). AAMAS 2016: 1333-1334 - [c90]Kengo Osaka, Fujio Toriumi, Toshiharu Sugawara:
Effect of Direct Reciprocity on Continuing Prosperity of Social Networking Services. COMPLEX NETWORKS 2016: 411-422 - [c89]Masashi Hayano, Yuki Miyashita, Toshiharu Sugawara:
Adaptive Switching Behavioral Strategies for Effective Team Formation in Changing Environments. ICAART (Revised Selected Papers) 2016: 37-55 - [c88]Masashi Hayano, Yuki Miyashita, Toshiharu Sugawara:
Switching Behavioral Strategies for Effective Team Formation by Autonomous Agent Organization. ICAART (1) 2016: 56-65 - [c87]Ayumi Sugiyama, Vourchteang Sea, Toshiharu Sugawara:
Effective Task Allocation by Enhancing Divisional Cooperation in Multi-Agent Continuous Patrolling Tasks. ICTAI 2016: 33-40 - [c86]ChiaWei Yeh, Toshiharu Sugawara:
Solving Coalition Structure Generation Problem with Double-Layered Ant Colony Optimization. IIAI-AAI 2016: 65-70 - [c85]Kengo Saito, Toshiharu Sugawara:
Assignment Problem with Preference and an Efficient Solution Method Without Dissatisfaction. KES-AMSTA 2016: 33-44 - [c84]Ryosuke Shibusawa, Tomoaki Otsuka, Toshiharu Sugawara:
Spread of Cooperation in Complex Agent Networks Based on Expectation of Cooperation. PRIMA 2016: 76-91 - [c83]Naoki Iijima, Masashi Hayano, Ayumi Sugiyama, Toshiharu Sugawara:
Analysis of task allocation based on social utility and incompatible individual preference. TAAI 2016: 24-31 - 2015
- [j15]Keisuke Yoneda, Ayumi Sugiyama, Chihiro Kato, Toshiharu Sugawara:
Learning and relearning of target decision strategies in continuous coordinated cleaning tasks with shallow coordination. Web Intell. 13(4): 279-294 (2015) - [c82]Kengo Saito, Toshiharu Sugawara:
Single-object resource allocation in multiple bid declaration with preferential order. ICIS 2015: 341-347 - [c81]Yuki Miyashita, Masashi Hayano, Toshiharu Sugawara:
Formation of Association Structures Based on Reciprocity and Their Performance in Allocation Problems. COIN@AAMAS/IJCAI 2015: 262-281 - [c80]Vourchteang Sea, Toshiharu Sugawara:
Area Partitioning Method with Learning of Dirty Areas and Obstacles in Environments for Cooperative Sweeping Robots. IIAI-AAI 2015: 523-529 - [c79]Yumeno Shiba, Haruna Umegaki, Toshiharu Sugawara:
Fair Assessment of Group Work by Mutual Evaluation with Irresponsible and Collusive Students Using Trust Networks. PRIMA 2015: 528-537 - [c78]Ayumi Sugiyama, Toshiharu Sugawara:
Meta-strategy for cooperative tasks with learning of environments in multi-agent continuous tasks. SAC 2015: 494-500 - [c77]Yuki Miyashita, Masashi Hayano, Toshiharu Sugawara:
Self-Organizational Reciprocal Agents for Conflict Avoidance in Allocation Problems. SASO 2015: 150-155 - [c76]Ryutaro Kawaguchi, Masashi Hayano, Toshiharu Sugawara:
Balanced Team Formation for Tasks with Deadlines. WI-IAT (2) 2015: 234-241 - 2014
- [j14]Masashi Hayano, Dai Hamada, Toshiharu Sugawara:
Role and member selection in team formation using resource estimation for large-scale multi-agent systems. Neurocomputing 146: 164-172 (2014) - [j13]Kazuki Urakawa, Toshiharu Sugawara:
Learning of Task Allocation Method Based on Reorganization of Agent Networks in Known and Unknown Environments. J. Inf. Process. 22(2): 289-298 (2014) - [c75]Ryosuke Shibusawa, Toshiharu Sugawara:
Norm Emergence via Influential Weight Propagation in Complex Networks. ENIC 2014: 30-37 - [c74]Yumeno Shiba, Toshiharu Sugawara:
Fair assessment of group work by mutual evaluation based on trust network. FIE 2014: 1-7 - [c73]Ayumi Sugiyama, Toshiharu Sugawara:
Autonomous Strategy Determination with Learning of Environments in Multi-agent Continuous Cleaning. PRIMA 2014: 455-462 - [c72]Yuki Hirahara, Fujio Toriumi, Toshiharu Sugawara:
Evolution of Cooperation in SNS-norms Game on Complex Networks and Real Social Networks. SocInfo 2014: 112-120 - [c71]Toshiharu Sugawara:
Emergence of Conventions for Efficiently Resolving Conflicts in Complex Networks. WI-IAT (3) 2014: 222-229 - 2013
- [j12]Yoshiki Kanda, Romain Fontugne, Kensuke Fukuda, Toshiharu Sugawara:
ADMIRE: Anomaly detection method using entropy-based PCA with three-step sketches. Comput. Commun. 36(5): 575-588 (2013) - [j11]Dai Hamada, Toshiharu Sugawara:
Autonomous decision on team roles for efficient team formation by parameter learning and its evaluation. Intell. Decis. Technol. 7(3): 163-174 (2013) - [c70]Yuta Kazato, Kensuke Fukuda, Toshiharu Sugawara:
Towards classification of DNS erroneous queries. AINTEC 2013: 25-32 - [c69]Yuki Hirahara, Fujio Toriumi, Toshiharu Sugawara:
Evolution of Cooperation in Meta-Rewards Games on Networks of WS and BA Models. Web Intelligence/IAT Workshops 2013: 126-130 - [c68]Keisuke Yoneda, Chihiro Kato, Toshiharu Sugawara:
Autonomous Learning of Target Decision Strategies without Communications for Continuous Coordinated Cleaning Tasks. IAT 2013: 216-223 - [c67]Toshiharu Sugawara:
Task Allocation Strategy Based on Variances in Bids for Large-Scale Multi-Agent Systems. AIAI 2013: 110-120 - [c66]Masashi Hayano, Dai Hamano, Toshiharu Sugawara:
Role and Member Selection in Team Formation Using Resource Estimation. KES-AMSTA 2013: 125-136 - [c65]Chihiro Kato, Toshiharu Sugawara:
Decentralized Area Partitioning for a Cooperative Cleaning Task. PRIMA 2013: 470-477 - 2012
- [c64]Kazuki Urakawa, Toshiharu Sugawara:
Reorganization of Agent Networks with Reinforcement Learning Based on Communication Delay. IAT 2012: 324-331 - [c63]