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.

A ring-based architectural model for middle agents in agent-based system

In agent-based systems, the performance of middle agents not only relies on the matchmaking algorithms employed by them, but also the architecture that organizes them with suitable organizational structure and coordination mechanism. In this paper, we contribute a framework and develop a couple of middle agents with logical ring organizational structure to match requester agents with service provider agents. The middle agent is of the features of proliferation and self-cancellation according to the sensory input from its environment. The token-based coordination mechanism of middle agents is designed. Two kinds of middle agents, namely, host and duplicate, are designed for promoting the scalability and robustness of agent-based systems. We demonstrate the potentials of the architecture by case study.

3D haptic needle insertion simulator utilising an agent based spherical voxel model

This paper describes a technique for the real-time modeling of deformable tissue. Specifically geared towards needle insertion simulation, the low computational requirements of the model enable highly accurate haptic feedback to a user without introducing noticeable time delay or buzzing generally associated with haptic surgery simulation. Using a spherical voxel array combined with aspects of computational geometry and agent communication and interaction principals, the model is capable of providing haptic update rates of over 1000Hz with real-time visual feedback. Iterating through over 1000 voxels per millisecond to determine collision and haptic response while making use of Vieta’s Theorem for extraneous force culling.

Decision aggregation in an agent-based financial investment planning system

Agent technology provides a new way to model many complex problems like financial investment planning. With this observation in mind, a financial investment planning system was developed from agent perspectives with 12 different agents integrated. Some of the agents have similar problem solving and decision making capabilities. The results from these agents require to be combined. Ordered Weighted Averaging (OWA) operator was chosen to aggregate different results. Details on how OWA was applied as well as appropriate evaluation are presented.

Multi-agent model for robotic assembly system

In this paper, a multi-agent based model for a robotic assembly system is presented. Firstly, an organization model is used to construct the multi-agent model. Secondly, a dynamic self-organizing method is then put forward for the multi-agent robotic system to bid and contract the operations. Thirdly, a real multi-agent robotic system is built and assembly experiments are carried out. Finally, the experimental results confirm that the present multi-agent robotic system has flexibility, adaptation and stability.

An agent-based hybrid intelligent system for foreign exchange trading

The foreign exchange (FX) market has many features including (1) Each trader’s payoff depends not only on his own behavior, but also on other traders’ decisions; (2) The number of traders is too large to make them all know the other dealers’ methods of decision making; and (3) The FX market has many levels. The FX market is complex because of these features. A diversity of techniques are required to deal with such complex problems. That is hybrid solutions are crucial for the FX market. On the other hand, research into the FX market has revealed that it demonstrates some characteristics of multi-agent systems such as autonomy, interaction, and emergence. To this end, an agent-based hybrid intelligent system was developed for FX trading, which is based on our proposed agent-based hybrid framework. This paper is to discuss the analysis, design, and implementation such a system. Some experimental results and comparisons with related works are also provided. The interest of this paper does not reside in improving the predictive capabilities of different FX models, but rather in how to integrate different models into one system under the unifying agent framework. The success of this system indicates that agent perspectives are very appropriate to model complex problems such as the FX trading.

An agent-based framework for petroleum information services from distributed heterogeneous data resources

For making good decisions in the area of petroleum production, it is becoming a big problem how to timely gather sufficient and correct information, which may be stored in databases, data files, or on the World Wide Web. In this paper, Gaia methodology and Open Agent Architecture were employed to contribute a framework to solve above problem. The framework consists of three levels, namely, role mode, agent type, and agent instance. The model with five roles is analyzed. Four agent types are designed Six agent instances are developed for constructing the system of petroleum information services. The experimental results show that all agents in the system can work cooperatively to organize and retrieve relevant petroleum information. The successful implementation of the framework shows that agent-based technology can significantly facilitate the construction of complex systems in distributed heterogeneous data resource environment.

A platform for dynamic organization of agents in agent-based systems

In most agent-based systems, different middle agents are employed to increase their flexibility. However, there are still three issues remain unsolved. In centralized architecture with single middle agent, the middle agent itself is a bottleneck and suffers from single point failure; middle agents in distributed architecture lack capability of dynamic organization of agents; The reliability is not strong because of the single point failure and lack of effective architecture. We introduce a platform with ring architectural model to solve all above problems. In the platform, multiple middle agents are dynamically supported for solving the first problem. For solving the second problem, middle agents dynamically manage the registration and cancellation of service provider agents and application teams, each of which includes a set of closely interacting requester agents to complete an independent task. Redundancy middle agent technique is proposed for solving the third problem. All middle agents are of the feature of proliferation and self-cancellation according to the sensory inputs from their environment. For organizing the middle agents effectively, a ring architectural model is proposed. We demonstrate the applicability of the platform by its application and present experimental evidence that the platform is flexible 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.

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.

Trade and industrial policy in developing countries : what scope for interfaces between agent-based models and computable-general equilibrium models

How best to assess trade and industrial policy in developing countries is a controversial question that unlocks a host of modelling complexities. Large computable general-equilibrium (CGE) models dominate many economic policy debates, but recent developments in the field have demonstrated that it is by no means clear that they give reliable results to questions of how trade reforms affect the poor. Over the last decade or so, a new approach to modelling complex systems has emerged using agent-based models (ABMs). This paper explores the question of whether ABMs are useful for economic policy-makers seeking to quantitatively model the effects of trade and industrial policies and whether constructive interfaces could be developed between CGE models and ABMs. The paper argues that in developing economic policy, ABMs can and should be used in conjunction with CGE models and that there is much to be gained from a greater understanding of the strengths and weaknesses of different modelling approaches, and what domains are most appropriate for their use. It concludes with some reflections on the reasons for the success of CGE approaches and ways in which ABMs could be made more widely understood and used among economists.

Ethical trust and social moral norms simulation : a bio-inspired agent-based modelling approach

The understanding of the micro-macro link is an urgent need in the study of social systems. The complex adaptive nature of social systems adds to the challenges of understanding social interactions and system feedback and presents substantial scope and potential for extending the frontiers of computer-based research tools such as simulations and agent-based technologies. In this project, we seek to understand key research questions concerning the interplay of ethical trust at the individual level and the development of collective social moral norms as representative sample of the bigger micro-macro link of social systems. We outline our computational model of ethical trust (CMET) informed by research findings from trust, machine ethics and neural science. Guided by the CMET architecture, we discuss key implementation ideas for the simulations of ethical trust and social moral norms.

Interplay of ethical trust and social moral norms : environment modelling and computational mechanisms in agent-based social simulation

In many agent-based models theoretical and computational mechanisms are needed for model abstraction and design. However, it can be challenging to arrive at the appropriate mechanisms and models. This research on the interplay of ethical trust and social moral norms addresses that challenge via an analytical framework on the spread of moral norms, the modelling of social environment and the selection of spread mechanisms as applied to agent-based social simulation. We describe the mechanism alignment mapping, two forms of interaction modelling between the social environment and agents, and the results obtained from the simulation of our computational model. These results provide an insight into how the agent-based paradigm can be applied as a technique of investigation for normative moral processes in computational social sciences.

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

An agent-based hybrid framework for database mining

While knowledge discovery in databases (KDD) is defined as an iterative sequence of the following steps: data pre-processing, data mining, and post data mining, a significant amount of research in data mining has been done, resulting in a variety of algorithms and techniques for each step. However, a single data-mining technique has not been proven appropriate for every domain and data set. Instead, several techniques may need to be integrated into hybrid systems and used cooperatively during a particular data-mining operation. That is, hybrid solutions are crucial for the success of data mining. This paper presents a hybrid framework for identifying patterns from databases or multi-databases. The framework integrates these techniques for mining tasks from an agent point of view. Based on the experiments conducted, putting different KDD techniques together into the agent-based architecture enables them to be used cooperatively when needed. The proposed framework provides a highly flexible and robust data-mining platform and the resulting systems demonstrate emergent behaviors although it does not improve the performance of individual KDD techniques.