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Multiagent Decision Making For Maritime Traffic Management

Arambam James Singh, Duc Thien Nguyen, Akshat Kumar, Hoong Chuin Lau
We address the problem of maritime traffic management in busy waterways to increase the safety of navigation by reducing congestion.  ...  We model maritime traffic as a large multiagent systems with individual vessels as agents, and VTS authority as the regulatory agent.  ...  Acknowledgments This research is supported by the Agency for Science, Technology and Research (A*STAR), Fujitsu Limited and the National Research Foundation Singapore as part of the A*STAR-Fujitsu-SMU  ... 
doi:10.1609/aaai.v33i01.33016171 fatcat:c422mw4lcffw3nrufdxeleyv5q

Multiagent Decision Making and Learning in Urban Environments

Akshat Kumar
2019 Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence  
In this paper, I will overview some of our recent contributions towards developing planning and reinforcement learning strategies to address several such challenges present in large-scale urban multiagent  ...  I also thank the UNi-CEN center at SMU ( for providing a conducive environment.  ...  Similarly, for maritime traffic, e-navigation aims to improve the management of the sea traffic by digitizing both on-board marine information and the communication between vessels and maritime traffic  ... 
doi:10.24963/ijcai.2019/895 dblp:conf/ijcai/Kumar19 fatcat:m7pe5nx2pfehndnmbyvk2hyete

Emerging Cyber risk Challenges in Maritime Transportation

Jussi Simola, Jouni Pöyhönen
2022 International Conference on Cyber Warfare and Security (ICIW)  
Maritime security and surveillance have become one of the main areas in managing overall situational awareness.For example, the growing importance of maritime traffic in cross-border trade has created  ...  Cybersituational awareness is an essential part of the management of maritime situational awareness.  ...  After this, the work will continue towards answering the main research question of the SMART project: How can a comprehensive cyber security architecture for smart port terminal be developed?  ... 
doi:10.34190/iccws.17.1.46 fatcat:td2s6ly4wratjfsxboefmo5jme

Designing Multiagent-Based Education Systems for Navigation Training

Chunsheng Yang, Hong Lin, Fuhua Oscar Lin
2006 2006 5th IEEE International Conference on Cognitive Informatics  
metaphor, and the knowledge-based decision-making support for intelligent agents.  ...  The presented approach for designing multiagent-based systems is not only useful for education systems but also for other multiagent-based applications such as multirobotic systems.  ...  Sheng-long Kao of the National Taiwan Ocean University for providing us ECID figures and the design requirements for MGIS support agent. The special thank goes to Bob Orchard for his proofreading.  ... 
doi:10.1109/coginf.2006.365536 dblp:conf/IEEEicci/YangLL06 fatcat:cox4fbmylzffxfdeoxnxrgl3x4

An Agent-Based Solution for the Berth Allocation Problem

Claudio Cubillos, René Díaz, Enrique Urra, Daniel Cabrera-Paniagua, Guillermo Cabrera, Gastón Lefranc
2013 International Journal of Computers Communications & Control  
The architecture modeling was done using PASSI methodology for the design of agent-oriented systems, and the implementation was done in JADE, a Javabased development environment for multiagent systems.  ...  This work presents the development of MABAP, a decision support system based on the agent technology that helps in solving the problem of berth allocation for ships within a port.  ...  As early described, for each berth request coming for a ship the Dock agent makes a callfor-bids to the available BerthPlanner agents in charge of managing the ships' schedule of each berth.  ... 
doi:10.15837/ijccc.2013.3.465 fatcat:stoye4v5prdsdnqojvovdlceou

An Overview of Recent Application Trends at the AAMAS Conference: Security, Sustainability and Safety

Manish Jain, Bo An, Milind Tambe
2012 The AI Magazine  
Sarvapali Ramchurn for the example of the smart-grid.  ...  Multiagent Traffic Management The increasing demand for mobility in our society has led to the more serious problem of traffic congestion.  ...  AI and multiagent techniques have been proposed for traffic management (see (Klugl and Bazzan 2011; Bazzan 2009 ) for a survey).  ... 
doi:10.1609/aimag.v33i3.2420 fatcat:aiebij2arvcyzar5pcskv6awke


Alfred Mwango Charo
2021 African Journal of Empirical Research  
However, the implementation of these maritime security frameworks and responses continue to face challenges, making them tend to be not so much effective in dealing with the maritime threats in Kenya's  ...  maritime jurisdiction.  ...  and how do their decision-making undermine or enhance the roles of your organizations?"  ... 
doi:10.51867/ajer.v2i1.18 fatcat:n4h5xvmbovglzmayjwp6oq5aau

Independent Reinforcement Learning for Weakly Cooperative Multiagent Traffic Control Problem [article]

Chengwei Zhang and Shan Jin and Wanli Xue and Xiaofei Xie and Shengyong Chen and Rong Chen
2021 arXiv   pre-print
Recently, reinforcement learning (RL) has achieved marked successes in managing sequential decision making problems, which motivates us to apply RL in the ASTC problem.  ...  The adaptive traffic signal control (ATSC) problem can be modeled as a multiagent cooperative game among urban intersections, where intersections cooperate to optimize their common goal.  ...  Recently, reinforcement learning (RL) has achieved marked successes in managing sequential decision making problems, which motivates us to apply RL in the traffic control problem.  ... 
arXiv:2104.10917v1 fatcat:f2pinj66xrfgvk56tgfmkiacqa

The Event Management Problem in a Container Terminal

Lorena Bearzotti, Rosa Gonzalez, Pablo Miranda
2013 Journal of Applied Research and Technology  
This paper presents a multiagent model to solve the event management problem; this problem has a number of features which makes the agent a suitable technology to consider applying.  ...  The model presented is the basis for developing a tool for the event management process in order to contribute to the reduction of logistics cost and to enhance the competitiveness of the container terminal  ...  decision making.  ... 
doi:10.1016/s1665-6423(13)71518-9 fatcat:o7vdbvjguvbzzpihtgamb3ipda

Towards Simulation-Aided Design of Multi-Agent Systems [chapter]

Michal Pěchouček, Michal Jakob, Peter Novák
2012 Lecture Notes in Computer Science  
Besides describing the capstones of the SADMAS approach and consequences of its application, we also illustrate it's use on a case-study of a next-generation decentralised air traffic management system  ...  With the growing complexity of multi-agent applications and environments in which they are deployed, there is a need for development techniques that would allow for early testing and validation of application  ...  As far as the application design is concerned, we argue that in the multiagent systems context, the initial application design should strive for maximum decentralisation of decision making of the application  ... 
doi:10.1007/978-3-642-28939-2_1 fatcat:imegulle7vgiboefvem73miejm

Trends in Models and Algorithms for Fleet Management

Maurizio Bielli, Alessandro Bielli, Riccardo Rossi
2011 Procedia - Social and Behavioral Sciences  
making processes (Ahuja and Liebchen, 2011).  ...  Many of them, however, operate essentially in a demand-responsive mode: the demands for services are not known beforehand and the fleet has to be deployed and managed (re-routed) in real-time to handle  ...  A different approach proposed by Belmonte et al. (2008) is based on the design and implementation of a multiagent decision support system for the bus fleet management domain.  ... 
doi:10.1016/j.sbspro.2011.08.004 fatcat:7tgw664otbcobbqxlz2iirlehy

Synergistic Integration Between Machine Learning and Agent-Based Modeling: A Multidisciplinary Review

Wei Zhang, Andrea Valencia, Ni-Bin Chang
2021 IEEE Transactions on Neural Networks and Learning Systems  
Agent-based modeling (ABM) involves developing models in which agents make adaptive decisions in a changing environment.  ...  Machine-learning (ML) based inference models can improve sequential decision-making by learning agents' behavioral patterns.  ...  [168] used online Q-learning for macrolevel decision-making in a MAS-based traffic signal control system to reduce the total travel time and delay of vehicles, and tests of different traffic scenarios  ... 
doi:10.1109/tnnls.2021.3106777 pmid:34473633 fatcat:vck4a2o7wbcl5ai6ntbdjvoigm

Guest Editorial: Special Issue on Enabling Massive IoT With 6G: Applications, Architectures, Challenges, and Research Directions

Shahid Mumtaz, Varun G. Menon, Anwer Al-Dulaimi, Muhammad Ikram Ashraf, Mohsen Guizani
2021 IEEE Internet of Things Journal  
We would like to express our sincere thanks to all the authors for submitting their articles and to the reviewers for their valuable comments and suggestions that significantly enhanced the quality of  ...  We hope that this special issue will serve as a useful reference for researchers, scientists, engineers, and academics in the field of massive IoT with 6G.  ...  In "Distributed probabilistic offloading in edge computing for 6G-enabled massive Internet of Things," Liao et al. investigate the challenges for edge computing in 6G, especially on making offloading decisions  ... 
doi:10.1109/jiot.2021.3061231 fatcat:pqsf5wqmv5gdfjxilm56sszpom

Exploiting the Use of Cooperation in Self-Organizing Reliable Multiagent Systems

Sebnem Bora
2018 Computing and informatics  
The Adaptive Multiagent Systems theory is applied to design adaptive groups of agents in order to build reliable multiagent systems.  ...  In this paper, a novel and cooperative approach is exploited introducing a self-organizing engine to achieve high reliability and availability in multiagent systems.  ...  However, during the decision process, the leader exploits only its local information when making a decision about the change in the agent's criticality.  ... 
doi:10.4149/cai_2018_6_1363 fatcat:jcl4qhefwrdupoxhpjdxb7bqwu

A Multi-agent Approach to Model and Analyze the Behavior of Vessels in the Maritime Domain

Mathias Anneken, Yvonne Fischer, Jürgen Beyerer
2017 Proceedings of the 9th International Conference on Agents and Artificial Intelligence  
First results for this algorithm are shown by using examples from the maritime domain. On the one hand, the algorithm is used to calculate an anomaly score.  ...  Consequently, it is implied, that the objects are cooperating in order to achieve an optimal result for themselves.  ...  The authors are responsible for the content of this article.  ... 
doi:10.5220/0006192002000207 dblp:conf/icaart/AnnekenFB17 fatcat:4izk7podgbapnglkkfanzhnbby
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