MASE-BDI: agent-based simulator for environmental land change with efficient and parallel auto-tuning

2016 ◽  
Vol 45 (3) ◽  
pp. 904-922 ◽  
Author(s):  
Cássio G. C. Coelho ◽  
Carolina G. Abreu ◽  
Rafael M. Ramos ◽  
Aldo H. D. Mendes ◽  
George Teodoro ◽  
...  
Keyword(s):  
Land Change ◽  
Agent Based ◽  
Bdi Agent ◽  
Auto Tuning

Exploring Agent-Based Modeling for Emergency Logistics Collaborative Decision Making

2013 ◽  
Vol 710 ◽  
pp. 781-785 ◽  
Author(s):  
Li Zhang ◽  
Zhi Qi ◽  
Hao Cui ◽  
Sen Hua Wang ◽  
Ya Hui Ning ◽  
...  
Keyword(s):  
Decision Making ◽  
Local Level ◽  
Collaborative Decision Making ◽  
Agent Based ◽  
Concept Model ◽  
Emergency Logistics ◽  
Bdi Agent ◽  
Distribution Process ◽  
Multi Agent ◽  
Collaborative Decision

Aiming at the requirements of urgency and dynamics in emergency logistics, this paper presents a multi-agent system (MAS) concept model for emergency logistics collaborative decision making. The suggested model includes three kinds of agents, i.e., role agent, function agent and assistant agent. Role agent excutes emergency logistics activities, function agent achieves the task requirements in every work phase and assistant agent helps organizing and visiting data. Two levels agent views serve as the basic skeleton of the MAS. Top level is the global decision-making view, which describes the task distribution process with multiple agents. Local level is the execution planning view, which simulates task executing process of the performer. Finally, an extended BDI agent structure model is proposed to help the implementation at application level.

Progress of agent-based agricultural land change modeling: a review

2013 ◽  
Vol 33 (6) ◽  
pp. 1690-1700 ◽  
Author(s):  
余强毅 YU Qiangyi ◽  
吴文斌 WU Wenbin ◽  
杨鹏 YANG Peng ◽  
唐华俊 TANG Huajun ◽  
周清波 ZHOU Qingbo ◽  
...  
Keyword(s):  
Agricultural Land ◽  
Land Change ◽  
Agent Based ◽  
Land Change Modeling

scholarly journals DESIGNING A BDI AGENT REACTANT MODEL OF BEHAVIOURAL CHANGE INTERVENTION

2015 ◽  
Vol 78 (2-2) ◽  
Author(s):  
Ojeniyi Adegoke ◽  
Azizi Ab Aziz ◽  
Yuhanis Yusof
Keyword(s):  
Behavioural Change ◽  
Psychological Reactance ◽  
Main Determinant ◽  
Agent Based ◽  
Agent Model ◽  
Design And Implementation ◽  
Psychological Theories ◽  
Bdi Agent ◽  
Behavioural Factors ◽  
Generic Representation

Belief-Desire-Intention (BDI) model is well suited for describing agent’s mental state. The BDI of an agent represents its motivational stance and are the main determinant of agent’s actions. Therefore, explicit understanding of the representation and modelling of such motivational stance plays a central role in designing BDI agent with successful behavioural change interventions. Nevertheless, existing BDI agent models do not represent agent’s behavioural factors explicitly. This leads to a gap between design and implementation where psychological reactance has being identified as the cause of BDI agent behavioural change interventions failure. Hence, this paper presents a generic representation of BDI agent model based on behavioural change and psychological theories. Also, using mathematical analysis the model was evaluated. The objective of the proposed BDI agent model is to bridge the gap between agent design and implementation for successful agent-based interventions. The model will be realized in an agent-based application that motivates children towards oral hygiene. The study explicitly depicts how agent’s behavioural factors interact to enhance behaviour change which will assist agent-based intervention designers to be able to design intervention that will be void of reactance.

Mase

2017 ◽  
pp. 106-127 ◽  
Author(s):  
Celia G. Ralha ◽  
Carolina G. Abreu
Keyword(s):  
Land Use ◽  
Conceptual Model ◽  
Model Complexity ◽  
Land Change ◽  
Map Comparison ◽  
Agent Based ◽  
Change Models ◽  
Multi Agent ◽  
Definition Of ◽  
Simulation Parameters

This chapter presents research carried out under the MASE project, including the definition of a conceptual model to characterize the behavior of individuals that interact in the dynamics of land-use and cover change. A computational tool for analyzing environmental scenarios of land change was developed, called MASE - Multi-Agent System for Environmental Simulation. MASE enables agent-based simulation scenarios and integrates the influence of socio-economic and political dynamics through the interaction of agents with rules of land-use and planning policies and the environmental physical and spatial variables. MASE simulator was extended to implement the Belief-Desire-Intention (BDI) model, called MASE-BDI. MASE and MASE-BDI are discussed including the conceptual model complexity and statistical techniques of map comparison to land change models. Two real cases of the Brazilian Cerrado validate quantitative and qualitative aspects of MASE and MASE-BDI simulators. Finally, the authors present some auto-tuning aspects of adjusting simulation parameters of MASE-BDI.

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