Climate change impacts and adaptation in Bangladesh : an agent-based approach

Bangladesh exemplifies the complex challenges facing densely populated coastal regions. The
pressures on the country are immense: around 145 million people live within an area of just 145,000 sq-km at
the confluence of three major river systems: the Ganges, the Brahmaputra and the Meghna. While progress
has been made, poverty remains widespread, with around 39% of children under five malnourished. Most of
its land-mass lies below 10m above sea level with considerable areas at sea level, leading to frequent and
prolonged flooding during the monsoons. Sea level rise is leading to more flooding as storm surges rise off
higher sea levels, pushing further inland. Higher sea levels also result in salt-water intrusion into freshwater
coastal aquifers and estuaries, contaminating drinking water and farmland. Warmer ocean waters are also
expected to lead to an increase in the intensity of tropical storms.
Bangladesh depends on the South Asian summer monsoon for most of its rainfall which is expected to
increase, leading to more flooding. Climate scientists are also concerned about the stability of monsoon and
the potential for it to undergo a nonlinear phase shift to a drier regime. Bangladesh faces an additional
hydrological challenge in that the Ganges and Brahmaputra rivers both rise in the Himalaya-Tibetan Plateau
region, where glaciers are melting rapidly. The Intergovernmental Panel on Climate Change (IPCC)
concluded that rapid melting is expected to increase river flows until around the late-2030s, by which time
the glaciers are expected to have shrunk from their 1995 extent of 500,000 sq-km to an expected 100,000 sqkm.
After the 2030s, river flows could drop dramatically, turning the great glacier-fed rivers of Asia into
seasonal monsoon-fed rivers. The IPCC concluded that as a result, water shortages in Asia could affect more
than a billion people by the 2050s. Over the same period, crop yields are expected to decline by up to 30% in
South Asia due to a combination of drought and crop heat stress. Bangladesh is therefore likely to face
substantial challenges in the coming decades.
In order to adequately understand the complex, dynamic, spatial and nonlinear challenges facing Bangladesh,
an integrated model of the system is required. An agent-based model (ABM) permits the dynamic
interactions of the economic, social, political, geographic, environmental and epidemiological dimensions of
climate change impacts and adaptation policies to be integrated via a modular approach. Integrating these
dimensions, including nonlinear threshold events such as mass migrations, or the outbreak of conflicts or
epidemics, is possible to a far greater degree with an ABM than with most other approaches.
We are developing a prototype ABM, implemented in Netlogo, to examine the dynamic impacts on poverty,
migration, mortality and conflict from climate change in Bangladesh from 2001 to 2100. The model employs
GIS and sub-district level census and economic data and a coarse-graining methodology to allow model
statistics to be generated on a national scale from local dynamic interactions. This approach allows a more
realistic treatment of distributed spatial events and heterogeneity across the country. The aim is not to
generate precise predictions of Bangladesh’s evolution, but to develop a framework that can be used for
integrated scenario exploration. This paper represents an initial report on progress on this project. So far the
prototype model has demonstrated the desirability and feasibility of integrating the different dimensions of
the complex adaptive system and, once completed, is intended to be used as the basis for a more detailed
policy-oriented model.

Towards a market oriented approach: employer requirements and implications for undergraduate economics programs

The decline in enrolments in economics degrees and majors has been the focus of much concern in recent times. In 2001, two of the current researchers published a paper outlining a framework with which future investigation into this issue could be conducted. Essentially this paper argued that a market oriented approach, which takes into account the value students and employers place on economics studies may point the way to a solution to the problem. As a first step in developing such an approach it is necessary to determine what employers require of the economics graduates they hire. A survey was conducted in 2002. This paper presents the results of this survey and discusses some of the ramifications for the teaching of undergraduate economics.

Supporting adaptive learning in hypertext environment : an agent based approach

One problem for hypertext-based learning application is to control learning paths for different learning activities. This paper first introduces related concepts of hypertext learning state space, then proposes an agent based approach used to provide kinds of adaptation for learning activities. Examples are given while explaining ways to realizing adaptive instructions. Possible future directions are also discussed at the end of this paper.

An agent-based approach to value theory and wealth distribution in economics

Any attempt to model an economy requires foundational assumptions about the relations between prices, values and the distribution of wealth. These assumptions exert a profound influence over the results of any model. Unfortunately, there are few areas in economics as vexed as the theory of value. I argue in this paper that the fundamental problem with past theories of value is that it is simply not possible to model the determination of value, the formation of prices and the distribution of income in a real economy with analytic mathematical models. All such attempts leave out crucial processes or make unrealistic assumptions which significantly affect the results. There have been two primary approaches to the theory of value. The first, associated with classical economists such as Ricardo and Marx were substance theories of value, which view value as a substance inherent in an object and which is conserved in exchange. For Marxists, the value of a commodity derives solely from the value of the labour power used to produce it - and therefore any profit is due to the exploitation of the workers. The labour theory of value has been discredited because of its assumption that labour was the only ‘factor’ that contributed to the creation of value, and because of its fundamentally circular argument. Neoclassical theorists argued that price was identical with value and was determined purely by the interaction of supply and demand. Value then, was completely subjective. Returns to labour (wages) and capital (profits) were determined solely by their marginal contribution to production, so that each factor received its just reward by definition. Problems with the neoclassical approach include assumptions concerning representative agents, perfect competition, perfect and costless information and contract enforcement, complete markets for credit and risk, aggregate production functions and infinite, smooth substitution between factors, distribution according to marginal products, firms always on the production possibility frontier and firms’ pricing decisions, ignoring money and credit, and perfectly rational agents with infinite computational capacity. Two critical areas include firstly, the underappreciated Sonnenschein-Mantel- Debreu results which showed that the foundational assumptions of the Walrasian general-equilibrium model imply arbitrary excess demand functions and therefore arbitrary equilibrium price sets. Secondly, in real economies, there is no equilibrium, only continuous change. Equilibrium is never reached because of constant changes in preferences and tastes; technological and organisational innovations; discoveries of new resources and new markets; inaccurate and evolving expectations of businesses, consumers, governments and speculators; changing demand for credit; the entry and exit of firms; the birth, learning, and death of citizens; changes in laws and government policies; imperfect information; generalized increasing returns to scale; random acts of impulse; weather and climate events; changes in disease patterns, and so on. The problem is not the use of mathematical modelling, but the kind of mathematical modelling used. Agent-based models (ABMs), objectoriented programming and greatly increased computer power however, are opening up a new frontier. Here a dynamic bargaining ABM is outlined as a basis for an alternative theory of value. A large but finite number of heterogeneous commodities and agents with differing degrees of market power are set in a spatial network. Returns to buyers and sellers are decided at each step in the value chain, and in each factor market, through the process of bargaining. Market power and its potential abuse against the poor and vulnerable are fundamental to how the bargaining dynamics play out. Ethics therefore lie at the very heart of economic analysis, the determination of prices and the distribution of wealth. The neoclassicals are right then that price is the enumeration of value at a particular time and place, but wrong to downplay the critical roles of bargaining, power and ethics in determining those same prices.

A multi-agent incremental negotiation scheme for meetings scheduling

We present an agent-oriented approach to the meeting scheduling problem and propose an incremental negotiation scheme that makes use of a hierarchical structure of an individual agent's working knowledge. First, we formalise the meeting scheduling problem in a multi-agent context, then elaborate on the design of a common agent architecture of all agents in the system. As a result, each agent becomes a modularised computing unit yet possesses high autonomy and robust interface with other agents. The system reserves the meeting participants' privacy since there are no agents with dominant roles, and agents can communicate at an abstract level in their hierarchical structures

A study of train group operation multi-agent model oriented RITS

In this paper, aiming at describing interrelationships and communication mechanisms among agents based on a multi-agent framework of Railway Intelligent Transportation System (RITS), we construct the model about stations and trains in the system, which is called Agent-Oriented G-Net Train Group Operation Model (AGNTOM). The framework degrades the complexity of computation and makes the distribution of simulation system easy in design. The simulated experiments prove that the model provides an effective approach for dealing with communication problems in the system.

A scalable and robust framework for agent-based heterogeneous database operation

How to operate database efficiently and unfailingly in agent-based heterogeneous data source environment is becoming a big problem. In this paper, we contribute a framework and develop a couple of agent-oriented matchmakers with logical ring organization structure to match task agents' requests with middleware agents of databases. The middleware agent is a wrapper of a specific database and is run on the same server with the database management system. The matchmaker is of the features of proliferation and self-cancellation according to the sensory input from its environment. The ring-based coordination mechanism of matchmakers is designed. Two kinds of matchmakers, namely, host and duplicate, are designed for improving the scalability and robustness of agent-based system. The middleware agents are improved for satisfying the framework. We demonstrate the potentials of the framework by case study and present theoretical and empirical evidence that our approach is scalable and robust.

Agent-based hybrid framework for decision making on complex problems

Electronic commerce and the Internet have created demand for automated systems that can make complex decisions utilizing information from multiple sources. Because the information is uncertain, dynamic, distributed, and heterogeneous in nature, these systems require a great diversity of intelligent techniques including expert systems, fuzzy logic, neural networks, and genetic algorithms. However, in complex decision making, many different components or sub-tasks are involved, each of which requires different types of processing. Thus multiple such techniques are required resulting in systems called hybrid intelligent systems. That is, hybrid solutions are crucial for complex problem solving and decision making. There is a growing demand for these systems in many areas including financial investment planning, engineering design, medical diagnosis, and cognitive simulation. However, the design and development of these systems is difficult because they have a large number of parts or components that have many interactions. From a multi-agent perspective, agents in multi-agent systems (MAS) are autonomous and can engage in flexible, high-level interactions. MASs are good at complex, dynamic interactions. Thus a multi-agent perspective is suitable for modeling, design, and construction of hybrid intelligent systems. The aim of this thesis is to develop an agent-based framework for constructing hybrid intelligent systems which are mainly used for complex problem solving and decision making. Existing software development techniques (typically, object-oriented) are inadequate for modeling agent-based hybrid intelligent systems. There is a fundamental mismatch between the concepts used by object-oriented developers and the agent-oriented view. Although there are some agent-oriented methodologies such as the Gaia methodology, there is still no specifically tailored methodology available for analyzing and designing agent-based hybrid intelligent systems. To this end, a methodology is proposed, which is specifically tailored to the analysis and design of agent-based hybrid intelligent systems. The methodology consists of six models - role model, interaction model, agent model, skill model, knowledge model, and organizational model. This methodology differs from other agent-oriented methodologies in its skill and knowledge models. As good decisions and problem solutions are mainly based on adequate information, rich knowledge, and appropriate skills to use knowledge and information, these two models are of paramount importance in modeling complex problem solving and decision making. Follow the methodology, an agent-based framework for hybrid intelligent system construction used in complex problem solving and decision making was developed. The framework has several crucial characteristics that differentiate this research from others. Four important issues relating to the framework are also investigated. These cover the building of an ontology for financial investment, matchmaking in middle agents, reasoning in problem solving and decision making, and decision aggregation in MASs. The thesis demonstrates how to build a domain-specific ontology and how to access it in a MAS by building a financial ontology. It is argued that the practical performance of service provider agents has a significant impact on the matchmaking outcomes of middle agents. It is proposed to consider service provider agents' track records in matchmaking. A way to provide initial values for the track records of service provider agents is also suggested. The concept of ‘reasoning with multimedia information’ is introduced, and reasoning with still image information using symbolic projection theory is proposed. How to choose suitable aggregation operations is demonstrated through financial investment application and three approaches are proposed - the stationary agent approach, the token-passing approach, and the mobile agent approach to implementing decision aggregation in MASs. Based on the framework, a prototype was built and applied to financial investment planning. This prototype consists of one serving agent, one interface agent, one decision aggregation agent, one planning agent, four decision making agents, and five service provider agents. Experiments were conducted on the prototype. The experimental results show the framework is flexible, robust, and fully workable. All agents derived from the methodology exhibit their behaviors correctly as specified.

A decentralised multi-agent approach to enhance the stability of smart microgrids with renewable energy

This paper presents the impact of large penetration of wind power on the transient stability through a dynamic evaluation of the critical clearing times (CCTs) by using intelligent agent-based approach. A decentralised multi-agent-based framework is developed, where agents represent a number of physical device models to form a complex infrastructure for computation and communication. They enable the dynamic flow of information and energy for the interaction between the physical processes and their activities. These agents dynamically adapt online measurements and use the CCT information for relay coordination to improve the transient stability of power systems. Simulations are carried out on a smart microgrid system for faults at increasing wind power penetration levels and the improvement in transient stability using the proposed agent-based framework is demonstrated.

Agent-Based Hybrid Intelligent Systems: An Agent-Based Framework for Complex Problem Solving

Pt. I. Fundamentals of hybrid intelligent systems and agents -- 1. Introduction -- 2. Basics of hybrid intelligent systems -- 3. Basics of agents and multi-agent systems -- Pt. II. Methodology and framework -- 4. Agent-oriented methodologies -- 5. Agent-based framework for hybrid intelligent systems --6. Matchmaking in middle agents -- Pt. III. Application systems -- 7. Agent-based hybrid intelligent system for financial investment
planning -- 8. Agent-based hybrid intelligent system for data mining -- Pt. IV. Concluding remarks -- 9. The less the more -- App. Sample source codes of the agent-based financial planning system

Incorporating design explanation within formal object-oriented method (FOOM)

Requirements engineering is a commencing phase in the development of either software applications or information systems. It is concerned with understanding and specifying the customer's requirements of the system to be delivered. Throughout the literature, this is agreed to be one of the most crucial and, unfortunately, problematic phases in development. Despite the diversity of research directions, approaches and methods, the question of process understanding and management is still limited. Among contemporary approaches to the improvement of the current practice of Requirements Engineering, Formal Object-Oriented Method (FOOM) has been introduced as a new promising solution. The FOOM approach to requirements engineering is based on a synthesis of socio-organisational theory, the object-oriented approach, and mathematical formal specification. The entire FOOM specification process is evolutionary and involves a large volume of changes in requirements. During this process, requirements evolve through various forms of informal, semi-formal, and formal while maintaining a semantic link between these forms and, most importantly, conforming to the customer's requirements. A deep understanding of the complexity of the requirements model and its dynamics is critical in improving requirements engineering process management. This thesis investigates the benefits of documenting both the evolution of the requirements model and the rationale for that evolution. Design explanation explains and justifies the deliberations of, and decisions made during, the design activity. In this thesis, design explanation is used to describe the requirements engineering process in order to improve understandability of, and traceability within, the evolving requirements specification. The design explanation recorded during this research project is also useful in assisting the researcher in gaining insights into the creativity and opportunistic characteristics of the requirements engineering process. This thesis offers an interpretive investigation into incorporating design explanation within FOOM in order to extend and advantage the method. The researcher's interpretation and analysis of collected data highlight an insight-driven and opportunistic process rather than a strictly and systematically predefined one. In fact, the process was not smoothly evolutionary, but involved occasional 'crisis' points at which the model was reconceptualised, simplified and restructured. Therefore, contributions of the thesis lie not only in an effective incorporation of design explanation within FOOM, but also a deep understanding of the dynamic process of requirements engineering. The new understanding of the complexity of the requirements model and its dynamics suggests new directions for future research and forms a basis for a new approach to process management.

Service-oriented wireless sensor networks and an energy-aware mesh routing algorithm

Service-oriented wireless sensor networks (WSNs) are being paid more and more attention because service computing can hide complexity of WSNs and enables simple and transparent access to individual sensor nodes. Existing WSNs mainly use IEEE 802.15.4 as their communication specification, however, this protocol suite cannot support IP-based routing and service-oriented access because it only specifies a set of physical- and MAC-layer protocols. For inosculating WSNs with IP networks, IEEE proposed a 6LoWPAN (IPv6 over LoW Power wireless Area Networks) as the adaptation layer between IP and MAC layers. However, it is still a challenging task how to discover and manage sensor resources, guarantee the security of WSNs and route messages over resource-restricted sensor nodes. This paper is set to address such three key issues. Firstly, we propose a service-oriented WSN architectural model based on 6LoWPAN and design a lightweight service middleware SOWAM (service-oriented WSN architecture middleware), where each sensor node provides a collection of services and is managed by our SOWAM. Secondly, we develop a security mechanism for the authentication and secure connection among users and sensor nodes. Finally, we propose an energyaware mesh routing protocol (EAMR) for message transmission in a WSN with multiple mobile sinks, aiming at prolonging the lifetime of WSNs as long as possible. In our EAMR, sensor nodes with the residual energy lower than a threshold do not forward messages for other nodes until the threshold is leveled down. As a result, the energy consumption is evened over sensor nodes significantly. The experimental results demonstrate the feasibility of our service-oriented approach and lightweight middleware SOWAM, as well as the effectiveness of our routing algorithm EAMR.

Employer requirements of economics graduates and the implications for undergraduate economics programs

In recent years there has been considerable debate about the general decline in the number of students undertaking bachelor degrees and majors in economics. The discussion has stemmed mainly from a supply-side perspective of the economics education market. The goal of this paper is to add another dimension to the debate and report the results of a survey of employers of economics graduates. Drawing on the extensive customer services literature it is argued that a market oriented, or demand-side analysis is also an important component in redressing low student enrolments and retention. A first step in adopting a market oriented approach is to determine the skills required of the economics graduates entering the jobs market. With the support of The Economics Society of Au~tralia, twenty-nine public and private sector employers were surveyed in 2002. The aim of the survey was to establish the demand for economics graduates with bachelor and honours degrees, the skills and knowledge required of these graduates, and the performance of such graduates. The study found that economic knowledge and skill were important to employers. However, the skills rated most important by employers were the more general or 'generic' skills of clear writing, data analysis, interpersonal skills and a practical problem-solving orientation. While graduates generally performed satisfactorily in relation to the economic skills required by employers, this was not the case for generic skills. The result of the survey findings have some significant implications for the content and teaching of undergraduate economics programs. This paper outlines these implications and also discusses areas for future research It is argued that such research should aim to utilize both the demand and supplyside perspectives with the development of more precise definitions and measurement of the economic skills required by the various stakeholders in the economics education market.