A Multi-Agent Model for Countering Terrorism

2020 ◽  
Author(s):  
Oussama Kebir ◽  
Issam Nouaouri ◽  
Mouna Belhadj ◽  
Lamjed Bensaid
Keyword(s):  
Decision Making ◽  
Division Of Labour ◽  
Agent Model ◽  
Counter Terrorism ◽  
The Past ◽  
Asymmetric War ◽  
Multi Agent

The rise of terrorism over the past decade did not only hinder the development of some countries, but also it continues to destroy humanity. To face this concept of an emerging crisis, every country and every citizen is responsible for the fight against terrorism. As conventional plans became useless against terrorism, governments are required to establish innovative concepts and technologies to support units in this asymmetric war. In this paper, we propose a new multi-agent model for counter-terrorism characterized by a methodical process and a flexibility to handle different contingency scenarios. The division of labour in our multi-agent model improves decision making and the structuring of organisational plans.

scholarly journals An Intelligent Fleet Condition-Based Maintenance Decision Making Method Based on Multi-Agent

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Qiang Feng ◽  
Songjie Li ◽  
Bo Sun
Keyword(s):  
Decision Making ◽  
Condition Based Maintenance ◽  
Heuristic Rules ◽  
Layer Model ◽  
Agent Model ◽  
Intelligent Maintenance ◽  
Support Resources ◽  
Multi Agent ◽  
Maintenance Decision ◽  
Global And Local

According to the demand for condition-based maintenance online decision making among a mission oriented fleet, an intelligent maintenance decision making method based on Multi-agent and heuristic rules is proposed. The process of condition-based maintenance within an aircraft fleet (each containing one or more Line Replaceable Modules) based on multiple maintenance thresholds is analyzed. Then the process is abstracted into a Multi-Agent Model, a 2-layer model structure containing host negotiation and independent negotiation is established, and the heuristic rules applied to global and local maintenance decision making is proposed. Based on Contract Net Protocol and the heuristic rules, the maintenance decision making algorithm is put forward. Finally, a fleet consisting of 10 aircrafts on a 3-wave continuous mission is illustrated to verify this method. Simulation results indicate that this method can improve the availability of the fleet, meet mission demands, rationalize the utilization of support resources and provide support for online maintenance decision making among a mission oriented fleet.

scholarly journals Research on decision-making strategy of soccer robot based on multi-agent reinforcement learning

2020 ◽  
Vol 17 (3) ◽  
pp. 172988142091696
Author(s):  
Xiaoli Liu
Keyword(s):  
Decision Making ◽  
Reinforcement Learning ◽  
Learning Algorithm ◽  
Division Of Labour ◽  
Learning System ◽  
Selection Strategy ◽  
Multi Agent System ◽  
Soccer Robot ◽  
Agent System ◽  
Multi Agent

This article studies a multi-agent reinforcement learning algorithm based on agent action prediction. In multi-agent system, the action of learning agent selection is inevitably affected by the action of other agents, so the reinforcement learning system needs to consider the joint state and joint action of multi-agent based on this. In addition, the application of this method in the cooperative strategy learning of soccer robot is studied, so that the multi-agent system can pass through the environment. To realize the division of labour and cooperation of multi-robots, the interactive learning is used to master the behaviour strategy. Combined with the characteristics of decision-making of soccer robot, this article analyses the role transformation and experience sharing of multi-agent reinforcement learning, and applies it to the local attack strategy of soccer robot, uses this algorithm to learn the action selection strategy of the main robot in the team, and uses Matlab platform for simulation verification. The experimental results prove the effectiveness of the research method, and the superiority of the proposed method is validated compared with some simple methods.

Truth Matters: Cognitive Integrity as an Intervention for Self-Deception

2017 ◽  
Author(s):  
Eugenia Isabel Gorlin ◽  
Michael W. Otto
Keyword(s):  
Decision Making ◽  
Problem Solving ◽  
Autonomous Agents ◽  
Therapeutic Interventions ◽  
Empirical Validation ◽  
The Past ◽  
Adaptive Problem

To live well in the present, we take direction from the past. Yet, individuals may engage in a variety of behaviors that distort their past and current circumstances, reducing the likelihood of adaptive problem solving and decision making. In this article, we attend to self-deception as one such class of behaviors. Drawing upon research showing both the maladaptive consequences and self-perpetuating nature of self-deception, we propose that self-deception is an understudied risk and maintaining factor for psychopathology, and we introduce a “cognitive-integrity”-based approach that may hold promise for increasing the reach and effectiveness of our existing therapeutic interventions. Pending empirical validation of this theoretically-informed approach, we posit that patients may become more informed and autonomous agents in their own therapeutic growth by becoming more honest with themselves.

Research on multi-agent model based on track methodology of ontology building

2009 ◽  
Vol 29 (2) ◽  
pp. 412-415
Author(s):  
Qiang LU ◽  
Ming CHEN ◽  
Zhi-guang WANG
Keyword(s):  
Agent Model ◽  
Model Based ◽  
Multi Agent ◽  
Ontology Building

Evidence-based Assessment

2010 ◽  
pp. 76-98
Author(s):  
John Hunsley ◽  
Eric J. Mash
Keyword(s):  
Decision Making ◽  
Clinical Assessment ◽  
Assessment Process ◽  
Evidence Based ◽  
The Past ◽  
Specific Assessment ◽  
The Many ◽  
Selection Of ◽  
Made In

Evidence-based assessment relies on research and theory to inform the selection of constructs to be assessed for a specific assessment purpose, the methods and measures to be used in the assessment, and the manner in which the assessment process unfolds. An evidence-based approach to clinical assessment necessitates the recognition that, even when evidence-based instruments are used, the assessment process is a decision-making task in which hypotheses must be iteratively formulated and tested. In this chapter, we review (a) the progress that has been made in developing an evidence-based approach to clinical assessment in the past decade and (b) the many challenges that lie ahead if clinical assessment is to be truly evidence-based.

A Big Thank You to our Reviewers in the Past Year!

2021 ◽  
Vol 42 (02) ◽  
pp. 191-195
Keyword(s):  
Decision Making ◽  
Peer Review ◽  
Decision Making Process ◽  
The Past

Good reviewers are essential to the success of any journal and peer review is a major pillar of science. We are grateful to those mentioned below to have dedicated their time and expertise to help our authors improve and refine their manuscripts and support the Editor(s) in the decision making process in the past year.

scholarly journals Spending Political Capital*

2021 ◽  
Author(s):  
Arthur Campbell
Keyword(s):  
Decision Making ◽  
Incentive Contracts ◽  
Important Task ◽  
Political Capital ◽  
Alternative Mechanism ◽  
Team Size ◽  
Current Period ◽  
Multi Agent ◽  
Participation In Decision Making ◽  
Number Of Individuals

Abstract An important task for organizations is establishing truthful communication between parties with differing interests. This task is made particularly challenging when the accuracy of the information is poorly observed or not at all. In these settings, incentive contracts based on the accuracy of information will not be very effective. This paper considers an alternative mechanism that does not require any signal of the accuracy of any information communicated to provide incentives for truthful communication. Rather, an expert sacrifices future participation in decision-making to influence the current period’s decision in favour of their preferred project. This mechanism captures a notion often described as ‘political capital’ whereby an individual is able to achieve their own preferred decision in the current period at the expense of being able to exert influence in future decisions (‘spending political capital’). When the first-best is not possible in this setting, I show that experts hold more influence than under the first-best and that, in a multi-agent extension, a finite team size is optimal. Together these results suggest that a small number of individuals hold excessive influence in organizations.

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