scholarly journals An agent-based model to simulate tsetse fly distribution and control techniques: A case study in Nguruman, Kenya

2015 ◽  
Vol 314 ◽  
pp. 80-89 ◽  
Author(s):  
Shengpan Lin ◽  
Mark H. DeVisser ◽  
Joseph P. Messina
Keyword(s):  
Tsetse Fly ◽  
Agent Based Model ◽  
Agent Based ◽  
Control Techniques ◽  
And Control

scholarly journals Development of an agent-based model to assess the impact of substandard and falsified anti-malarials: Uganda case study

2019 ◽  
Vol 18 (1) ◽  
Author(s):  
Sachiko Ozawa ◽  
Daniel R. Evans ◽  
Colleen R. Higgins ◽  
Sarah K. Laing ◽  
Phyllis Awor
Keyword(s):  
Agent Based Model ◽  
Agent Based ◽  
The Impact

scholarly journals An agent-based model of tsetse fly response to seasonal climatic drivers: Assessing the impact on sleeping sickness transmission rates

2018 ◽  
Vol 12 (2) ◽  
pp. e0006188 ◽  
Author(s):  
Simon Alderton ◽  
Ewan T. Macleod ◽  
Neil E. Anderson ◽  
Gwen Palmer ◽  
Noreen Machila ◽  
...  
Keyword(s):  
Sleeping Sickness ◽  
Tsetse Fly ◽  
Agent Based Model ◽  
Agent Based ◽  
Transmission Rates ◽  
Climatic Drivers ◽  
The Impact

scholarly journals CystiSim – An Agent-Based Model for Taenia solium Transmission and Control

2016 ◽  
Vol 10 (12) ◽  
pp. e0005184 ◽  
Author(s):  
Uffe Christian Braae ◽  
Brecht Devleesschauwer ◽  
Sarah Gabriël ◽  
Pierre Dorny ◽  
Niko Speybroeck ◽  
...  
Keyword(s):  
Taenia Solium ◽  
Agent Based Model ◽  
Agent Based ◽  
And Control

scholarly journals A situation-based multi-agent architecture for handling misunderstandings in interactions

2015 ◽  
Vol 25 (3) ◽  
pp. 439-454 ◽  
Author(s):  
Thao Phuong Pham ◽  
Mourad Rabah ◽  
Pascal Estraillier
Keyword(s):  
Adaptive Systems ◽  
Agent Based ◽  
Consistency Management ◽  
Management Scenario ◽  
Multi Agent ◽  
Online Distance Learning ◽  
Online Distance ◽  
And Control ◽  
Elementary Building

AbstractDuring interactions, system actors may face up misunderstandings when their local states contain inconsistent data about the same fact. Misunderstandings in interactions are likely to reduce interactivity performances (deviation or deadlock) or even affect overall system behavior. In this paper, we characterize misunderstandings in interactions between system actors (that may be human users or system agents) in interactive adaptive systems. To deal with such misunderstandings and ensure state consistency, we present an agent-based architecture and a scenario structuring approach. The system includes several agents devoted to scenario unfolding, plot adaptation and consistency management. Scenario structuring is based on the notion of a situation that is an elementary building block dividing the interactions between systems’ actors into contextual scenes. This pattern supports not only scenario execution but consistency management as well. In order to organize and control interactions, the situation contextualizes interactions and activity of the system’s actors. It also includes prevention and tolerance agent-based mechanisms to deal with the misunderstandings and their causes. We validate our consistency management mechanisms using Uppaal simulation and provide some experimental results to show the effectiveness of our approach on an online distance learning case study

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