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Measuring Complexity of Multi-agent Simulations – An Attempt Using Metrics [chapter]

Franziska Klügl
2008 Lecture Notes in Computer Science  
In this contribution, I address this problem by introducing metrics for measuring properties of agent-based simulations for finally being able to characterize the complexities involved in developing such  ...  The variety of existing agent-based simulations is overwhelming.  ...  The aim of our attempt for defining metrics is basically to analyze and compare aspects of complexity of agent-based simulation.  ... 
doi:10.1007/978-3-540-85058-8_8 fatcat:urpggnr3tvg3lez6csz5crdkdm

SAMAS: Scalable Architecture for Multi-resolution Agent-Based Simulation [chapter]

Alok Chaturvedi, Jie Chi, Shailendra Mehta, Daniel Dolk
2004 Lecture Notes in Computer Science  
With the added complexity, the scalability of a simulation environment becomes a crucial measure of its ability in coping with the complexity of the underlying system.  ...  In this paper, we present the design of Samas, a highly scalable architecture for multi-resolution agent-based simulation.  ...  Agent-based simulation attempts to capture this complexity by using a large number of artificial agents, each of which plays the role of one or more of the elements in the real system.  ... 
doi:10.1007/978-3-540-24688-6_101 fatcat:rqgdgafutbfexpbgkc3dnywlrm

Network-based Metric for Measuring Combat Effectiveness
English

Youngwoo Lee, Taesik Lee
2014 Defence Science Journal  
An ability to measure combat effectiveness is critical to strategic and tactical decision making; however, it is a challenging task to develop an operational metric for combat effectiveness due to the  ...  Using a meta-network representation, two types of basic unit structures of attack opportunity -isolated and networked -are identified, which are then used as a basic element for measuring combat effectiveness  ...  ACKNOWLEDGMENT This work was supported by Defence Acquisition Program Administration and Agency for Defence Development of Korea under contract UD110006MD.  ... 
doi:10.14429/dsj.64.5534 fatcat:cxooyscaknbfjl7bnrq7j7j4ke

Resource Efficient Real-time Reliability Model for Multi-Agent IoT Systems

Ivan Eroshkin, Lukas Vojtech, Marek Neruda
2021 IEEE Access  
Virtualised microservices are mostly used in cloud-based IoT systems, which can be covered with multi-agent system (MAS) paradigm.  ...  Then, we evaluate time complexity and provide a measurement to demonstrate the reliability of the model application.  ...  The input metrics are computed as a ratio of successful attempts to all attempts or user expected attempts, which results in the dependency of the input data on history.  ... 
doi:10.1109/access.2021.3138931 fatcat:smx5akw6rrervh3kpaqf3v7vhm

Measuring collaborative emergent behavior in multi-agent reinforcement learning [article]

Sean L. Barton, Nicholas R. Waytowich, Erin Zaroukian, Derrik E. Asher
2018 arXiv   pre-print
Such a metric is useful for measuring collaboration between computational agents and may serve as a training signal for collaboration in future RL paradigms involving humans.  ...  Multi-agent reinforcement learning (RL) has important implications for the future of human-agent teaming.  ...  The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory  ... 
arXiv:1807.08663v1 fatcat:ud3ib2sd4bhftglmnk5morukoy

Introduction to autonomy control software

Henry Hexmoor, David Kortenkamp
2000 Journal of experimental and theoretical artificial intelligence (Print)  
Furthermore, the span of papers from theory-to system-driven and across many different domains provided our discussions with disparate perspectives on the development and use of metrics for autonomous  ...  It is most heartening that even the most theoretical of papers in this symposium are working with actual implementations.  ...  Bringing these concerns together, Paul Scerri and Nancy Reed provide the selection of an agent architecture for several simulation environments as an example of how metrics are used in practice.  ... 
doi:10.1080/095281300409784 fatcat:35bw5bbozvf2zmlxrqloo3ivkq

Evaluating Team Performance at the Edge of Chaos [chapter]

Mikhail Prokopenko, Peter Wang
2004 Lecture Notes in Computer Science  
This approach is a step towards a unified quantitative framework on behavioural and belief dynamics in complex multi-agent systems.  ...  The presented quantitative information-theoretic methods measure behavioural and epistemic entropy, and detect phase transitions -the edge of chaos -in team performance.  ...  Acknowledgements The authors are grateful to members of the "Entropy and self-organisation in multiagent systems" discussion group, and in particular to Mark Foreman, Ying Guo, Andrew Lampert, and Philip  ... 
doi:10.1007/978-3-540-25940-4_8 fatcat:yv55ecsctbffxcow7l6g5plrlq

Parameter estimation and comparative evaluation of crowd simulations

D. Wolinski, S. J. Guy, A.-H. Olivier, M. Lin, D. Manocha, J. Pettré
2014 Computer graphics forum (Print)  
We demonstrate the benefits of our framework for example-based simulation, modeling of cultural variations, artist-driven crowd animation, and relative comparison of some widely-used multi-agent simulation  ...  Our framework supports a variety of metrics to compare reference data and simulation outputs.  ...  The authors would also like to thank the Golaem company for their help preparing parts of the companion video.  ... 
doi:10.1111/cgf.12328 fatcat:qrs7fkskqng65lbj3rt44vnvci

What is scalability in multi-agent systems?

Omer F. Rana, Kate Stout
2000 Proceedings of the fourth international conference on Autonomous agents - AGENTS '00  
metrics can be identified to compare the relative performance of multi-agent systems.  ...  Scalability is an issue that becomes important when developing practical software agent systems, to perform some of the applications that agent development tools identify.  ...  PERFORMANCE METRICS In order to assess whether a given multi-agent system scales successfully, we need to identify metrics for measuring scalability.  ... 
doi:10.1145/336595.337033 dblp:conf/agents/RanaS00 fatcat:4zx4euezujalhmkef3aer2w5d4

Adversarial Reinforcement Learning Framework for Benchmarking Collision Avoidance Mechanisms in Autonomous Vehicles [article]

Vahid Behzadan, Arslan Munir
2018 arXiv   pre-print
in response to intentional collision attempts.  ...  agent, trained to drive the system into unsafe states.  ...  of interacting with an optimal adversarial agent.  ... 
arXiv:1806.01368v1 fatcat:pitfzjr2prbulfkw6b4fs2a66y

Computational modeling for reasoning about the social behavior of humans

Kathleen M. Carley
2008 Computational and mathematical organization theory  
This includes a computer program, or network of computers and programs, that attempt to operationalize an abstract model of the system.  ...  Keywords Dynamic network analysis · Social networks · Agent based models · Multi-agent simulation · Network science Introduction Computational modeling is a growth area in the social and behavioral sciences  ...  versus distributed multi-agent, local versus distributed, 7 system dynamic versus multi-agent versus multi-agent network.  ... 
doi:10.1007/s10588-008-9048-9 fatcat:5ejtl3e3fnd2bffynfqia4ku5a

MCjammer

Ilya Wagner, Valeria Bertacco
2008 Proceedings of the conference on Design, automation and test in Europe - DATE '08  
We accomplish this task through a distributed network of cooperating agents, which feed the processors with stimuli, each agent attempting to accomplish its own verification goals and support other agents  ...  The agents can dynamically change the stimuli based on coverage and pressure observed during simulation.  ...  The DFSM in each agent is used for an internal representation of coverage.  ... 
doi:10.1145/1403375.1403539 fatcat:76noqdjwtfgbdcxrliry7mfvbi

VECA: A New Benchmark and Toolkit for General Cognitive Development

Kwanyoung Park, Hyunseok Oh, Youngki Lee
2022 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
We present the VECA(Virtual Environment for Cognitive Assessment), which consists of two main components: (i) a first benchmark to assess the overall cognitive development of an AI agent, and (ii) a novel  ...  The developmental approach, simulating a cognitive development of a human, arises as a way to nurture a human-level commonsense and overcome the limitations of data-driven approaches.  ...  Using our toolkit, we developed a novel VECA benchmark that measures the overall cognitive development of an AI agent for the first time.  ... 
doi:10.1609/aaai.v36i1.19877 fatcat:r7uoukspqvfbde7opcfibqlr7u

A Robust, Distributed Task Allocation Algorithm for Time-Critical, Multi Agent Systems Operating in Uncertain Environments [chapter]

Amanda Whitbrook, Qinggang Meng, Paul W. H. Chung
2017 Lecture Notes in Computer Science  
The aim of this work is to produce and test a robust, distributed, multi-agent task allocation algorithm, as these are scarce and not well-documented in the literature.  ...  Variant A uses the expected value of the task completion times, variant B uses the worst-case scenario metric and variant C is a hybrid that implements a combination of these.  ...  The main aim of this work is to attempt to address some of these challenges by creating a robust, distributed, multi-agent task allocation system with a very low failure rate.  ... 
doi:10.1007/978-3-319-60045-1_8 fatcat:f6pcvf4hajftnfamlqh43stn4u

The Requirement Gatherers' Approach to the 2019 Multi-Agent Programming Contest Scenario [article]

Michael Vezina, Babak Esfandiari
2020 arXiv   pre-print
to each of our agents.  ...  The 2019 Multi-Agent Programming Contest (MAPC) scenario poses many challenges for agents participating in the contest.  ...  Metric 10: Opponent Rejected Submissions This single metric is used to measure the performance of the attacker agents.  ... 
arXiv:2006.02816v1 fatcat:uhfaxmowtjh67d5kgpifafzqae
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