Using simulation gaming to validate a mathematical modeling platform for resource allocation in disasters

The extraordinary conditions of a disaster require the mobilisation of all available resources, inducing the rush of humanitarian partners into the affected area This phenomenon called the proliferation of actors, causes serious problems during the disaster response phase including the oversupply, duplicated efforts, lack of planning In an attempt to reduce the partner proliferation problem a framework called PREDIS (PREdictive model for DISaster response partner selection) is put forward to configure the humanitarian network within early hours after disaster strike when the information is scarce To verify this model a simulation game is designed using two sets of real decision makers (experts and non-experts) in the disaster Haiyan scenario The result shows that using the PREDIS framework 100% of the experts could make the same decisions less than six hours comparing to 72 hours Also between 71% and 86% of the times experts and non-experts decide similarly using the PREDIS framewor

Climate change in game theory context

The aim of this paper is to survey the game theory modelling of the behaviour of global players in mitigation and adaptation related to climate change. Three main fields are applied for the specific aspects of temperature rise: behaviour games, CPR problem and negotiation games. The game theory instruments are useful in analyzing strategies in uncertain circumstances, such as the occurrence and impacts of climate change. To analyze the international players’ relations, actions, attitude toward carbon emission, negotiation power and motives, several games are applied for the climate change in this paper. The solution is surveyed, too, for externality problem

Climate change in game theory

The study provides an overview of the application possibilities of game theory to climate change. The characteristics of games are adapted to the topics of climate and carbon. The importance of uncertainty, probability, marginal value of adaptation, common pool resources, etc. are tailored to the context of international relations and the challenge of global warming

Computational intelligence based complex adaptive system-of-systems architecture evolution strategy

The dynamic planning for a system-of-systems (SoS) is a challenging endeavor. Large scale organizations and operations constantly face challenges to incorporate new systems and upgrade existing systems over a period of time under threats, constrained budget and uncertainty. It is therefore necessary for the program managers to be able to look at the future scenarios and critically assess the impact of technology and stakeholder changes. Managers and engineers are always looking for options that signify affordable acquisition selections and lessen the cycle time for early acquisition and new technology addition. This research helps in analyzing sequential decisions in an evolving SoS architecture based on the wave model through three key features namely; meta-architecture generation, architecture assessment and architecture implementation. Meta-architectures are generated using evolutionary algorithms and assessed using type II fuzzy nets. The approach can accommodate diverse stakeholder views and convert them to key performance parameters (KPP) and use them for architecture assessment. On the other hand, it is not possible to implement such architecture without persuading the systems to participate into the meta-architecture. To address this issue a negotiation model is proposed which helps the SoS manger to adapt his strategy based on system owners behavior. This work helps in capturing the varied differences in the resources required by systems to prepare for participation. The viewpoints of multiple stakeholders are aggregated to assess the overall mission effectiveness of the overarching objective. An SAR SoS example problem illustrates application of the method. Also a dynamic programing approach can be used for generating meta-architectures based on the wave model. --Abstract, page iii

Efficient performative actions for e-commerce agents

The foundational features of multi-agent systems are communication and interaction with other agents. To achieve these features, agents have to transfer messages in the predefined format and semantics. The communication among these agents takes place with the help of ACL (Agent Communication Language). ACL is a predefined language for communication among agents that has been standardised by the FIPA (Foundation for Intelligent Physical Agent). FIPA-ACL defines different performatives for communication among the agents. These performatives are generic, and it becomes computationally expensive to use them for a specific domain like e-commerce. These performatives do not define the exact meaning of communication for any specific domain like e-commerce. In the present research, we introduced new performatives specifically for e-commerce domain. Our designed performatives are based on FIPA-ACL so that they can still support communication within diverse agent platforms. The proposed performatives are helpful in modelling e-commerce negotiation protocol applications using the paradigm of multi-agent systems for efficient communication. For exact semantic interpretation of the proposed performatives, we also performed formal modelling of these performatives using BNF. The primary objective of our research was to provide the negotiation facility to agents, working in an e-commerce domain, in a succinct way to reduce the number of negotiation messages, time consumption and network overhead on the platform. We used an e-commerce based bidding case study among agents to demonstrate the efficiency of our approach. The results showed that there was a lot of reduction in total time required for the bidding process

Applying autonomy to distributed satellite systems: Trends, challenges, and future prospects

While monolithic satellite missions still pose significant advantages in terms of accuracy and operations, novel distributed architectures are promising improved flexibility, responsiveness, and adaptability to structural and functional changes. Large satellite swarms, opportunistic satellite networks or heterogeneous constellations hybridizing small-spacecraft nodes with highperformance satellites are becoming feasible and advantageous alternatives requiring the adoption of new operation paradigms that enhance their autonomy. While autonomy is a notion that is gaining acceptance in monolithic satellite missions, it can also be deemed an integral characteristic in Distributed Satellite Systems (DSS). In this context, this paper focuses on the motivations for system-level autonomy in DSS and justifies its need as an enabler of system qualities. Autonomy is also presented as a necessary feature to bring new distributed Earth observation functions (which require coordination and collaboration mechanisms) and to allow for novel structural functions (e.g., opportunistic coalitions, exchange of resources, or in-orbit data services). Mission Planning and Scheduling (MPS) frameworks are then presented as a key component to implement autonomous operations in satellite missions. An exhaustive knowledge classification explores the design aspects of MPS for DSS, and conceptually groups them into: components and organizational paradigms; problem modeling and representation; optimization techniques and metaheuristics; execution and runtime characteristics and the notions of tasks, resources, and constraints. This paper concludes by proposing future strands of work devoted to study the trade-offs of autonomy in large-scale, highly dynamic and heterogeneous networks through frameworks that consider some of the limitations of small spacecraft technologies.Postprint (author's final draft

Integration of decision support systems to improve decision support performance

Decision support system (DSS) is a well-established research and development area. Traditional isolated, stand-alone DSS has been recently facing new challenges. In order to improve the performance of DSS to meet the challenges, research has been actively carried out to develop integrated decision support systems (IDSS). This paper reviews the current research efforts with regard to the development of IDSS. The focus of the paper is on the integration aspect for IDSS through multiple perspectives, and the technologies that support this integration. More than 100 papers and software systems are discussed. Current research efforts and the development status of IDSS are explained, compared and classified. In addition, future trends and challenges in integration are outlined. The paper concludes that by addressing integration, better support will be provided to decision makers, with the expectation of both better decisions and improved decision making processes

An ontology-based spatial group decision support system for site selection application

This paper presents a new ontology-based multicriteria spatial group decision support system (GDSS) dedicated to site selection problems. Site selection is one of the most complex problems in the construction of a new building. It presents a crucial problem in terms of selecting the appropriate site among a group of decision makers with multiple alternatives (sites); in addition, the site must satisfy several criteria. To deal with this, the present paper introduces an ontology based multicriteria analysis method to solve semantic heterogeneity in vocabulary used by participants in spatial group decision support systems. The advantages of using ontology in GDSS are many: i) it enables the integration of heterogeneous sources of data available on the web and ii) it enables to facilitate meaning and sharing of data used in GDSS by participants. In order to facilitate cooperation and collaboration between participants in GDSS, our work aims to apply ontology at the model's structuration phase. The proposed system has been successfully implemented and exploited for a personalized environment