Behavior Of Individual Agents Research Articles

Study on the agile supply chain management based on agent

The most important task of the agile supply chain management (ASCM) is to reconfigure a supply chain based on the customers' requirement. Without more sophisticated cooperation and dynamic formation in an agile supply chain, it cannot be achieved for mass customization, rapid response and high quality services. Because of its great potential in supporting cooperation for the supply chain management, agent technology can carry out the cooperative work by inter-operation across networked human, organization and machines at the abstractive level in a computational system. A major challenge in building such a system is to coordinate the behavior of individual agent or a group of agents to achieve the individual and shared goals of the participants. In this paper, the agent technology is used to support modeling and coordinating of supply chain management.

Credit risk transfer, hedge funds, and the supply of liquidity

This paper provides a discussion about some recent issues related to the transfer of credit risk (CRT) from the perspective of global liquidity. The CRT market is enormously growing and exhibits major structural shifts in terms of buyers and sellers of protection. I try to address these issues from an options perspective by suggesting that liquidity providing can be understood, in economic terms, as selling put options. The overall conclusion of the paper is that it is not the extent of CRT per se, as often claimed, which causes liquidity related systemic risk, but rather the potential coordination failures of the behavior market participants in adverse market environments. In this context, I critically address the role of investments banks in providing liquidity to hedge funds, and finally, the (limited) access of global banks to central bank liquidity through cross-border collateral trading. Since coordination failures, seen as the major issue of a potential liquidity crisis, is to a large extent a matter of market structure, regulatory actions to improve liquidity should fo foccus on the architecture of the financial system in the first place, not so much on the behavior of individual agents. Market stabilization should therefore be understood as a process of establishing informative markets and adequate infrastructure.

Evolving cooperative bidding strategies in a power market

This paper presents an evolutionary algorithm to generate cooperative strategies for individual buyers in a competitive power market. The paper explores how buyers can lower their costs by using an evolutionary algorithm that evolves their group sizes and memberships. The evolutionary process uncovers interesting agent behaviors and strategies for collaboration. The developed agent-based model uses PowerWorld simulator to incorporate the traditional physical system characteristics and constraints while evaluating individual agent's behavior, actions and reactions on market dynamics. Simulation results on IEEE 14-bus system show that the evolutionary approach evolves mutually beneficial strategies that enhance the buyer's profitability. The buyers learn to achieve substantial cost savings by forming groups and adjusting their demand curves, without sacrificing much in desired power consumption.

Fundamental uncertainty and Keynes' probability theory

Within economic system agents daily make decisions. Those decisions are based on their expectations regarding future. Therefore, theoretical assumption about what do rational decision-makers really know about future and could agents make relatively reliable forecasts has colossal importance. Namely this assumption critically determines theoretical modeling of decision-making process. In economic theory we can make distinction between two opposite and irreconcilable standpoints on this issue. According to proponents of the Subjective Probability and the Rational Expectations Hypothesis future can be predicted exactly, that is, agents are able to mathematically calculate future precisely and to express it in terms of numbers. Consistently behavior of individual agent and society in aggregate can be predicted with great precision. On the other hand, Keynes, first economist who made clear distinction between risk and uncertainty, argued that past experiences and statistical analysis of past data were not reliable guide to future and that behavior of individual agents and society in aggregate could not be neither calculated exactly nor precisely predicted. Consequently, theoretical implications regarding decision-making and behavior of aggregate economic system of the two opposite standpoints are completely different.

When Does the Winner Take All in Two-Sided Markets?

We study the diffusion of competing two-sided networks using a differential game framework. We find that whether the winner takes all depends on the participation behaviour of individual agents on both sides of the market. When individual agents tend to participate in only one network, one network will dominate the market. As the tendency for joining multiple networks increases, the possibility for two networks to co-exist in the long-run also increases. Thus the steady-state market share of competing two-sided networks can be very different depending on adopters' choice of "multi-homing" or "single-homing".

NEW MODEL BASED ON CELLULAR AUTOMATA AND MULTIAGENT TECHNIQUES

The need for intelligent systems has grown in the past decade because of the increasing demand on humans and machines to perform better. The researchers of artificial intelligence (AI) have responded to these needs with the development of intelligent hybrid systems. This paper describes the modeling language for interacting hybrid systems in which we will build a new hybrid model of cellular automata and multiagent technology. Simulations with complex behavior will be model social dynamics where the focus is on the emergence of properties of local interactions. Therefore, in our approach, cellular automata form a useful framework for the multiagent simulation model and the model will be used for traffic system which lies in coordinating the local behavior of individual agent to provide an appropriate system-level behavior in grid of interacting organisms.

Design, development and validation of an agent-based model of electronic auctions

This paper presents the design, development and validation methodology of an agent-based computational model of the B2C electronic auction marketplace. It aims at a comprehensive understanding of the varied issues governing a B2C electronic auction, incorporating the behavior of all relevant agents such as the auctioneer, the consumer and the retailer; and the environment in which these agents operate and interact. In contrast with conventional methods, agent based modeling employs a bottom-up modeling approach where behaviors of individual agents and rules for their interaction, specified at the micro level, give rise to emergent macro level phenomenon. The development methodology should ensure that agent models are aligned with theory, current knowledge of the field and observed phenomena, and output validity of the model also needs to be ascertained. Beginning with a general introduction to agent based computational modeling, this paper formalizes this alignment and validation methodology and elaborates each step, noting the rationale and means for achieving these. The manner in which this process was used in modeling B2C auctions is then described.

Formal systems for persuasion dialogue

This article reviews formal systems that regulate persuasion dialogues. In such dialogues two or more participants aim to resolve a difference of opinion, each trying to persuade the other participants to adopt their point of view. Systems for persuasion dialogue have found application in various fields of computer science, such as non-monotonic logic, artificial intelligence and law, multi-agent systems, intelligent tutoring and computer-supported collaborative argumentation. Taking a game-theoretic view on dialogue systems, this review proposes a formal specification of the main elements of dialogue systems for persuasion and then uses it to critically review some of the main formal systems for persuasion. The focus of this review will be on regulating the interaction between agents rather than on the design and behaviour of individual agents within a dialogue.

Spatial microsimulation for rural policy analysis in Ireland: The implications of CAP reforms for the national spatial strategy

Microsimulation attempts to describe economic and social events by modelling the behaviour of individual agents. These models have proved useful in evaluating the impact of policy changes at the micro level. Spatial microsimulation models contain geographic information and allow for a regional or local approach to policy analysis. This paper builds on previous work on urban systems by employing similar modelling techniques for the analysis of rural areas [Birkin, M., Clarke, M., 1988. SYNTHESIS—a synthetic spatial information system for urban and regional analysis: methods and examples. Environment and Planning A 20, 1645–1671; Ballas, D. et al., 1999. Exploring microsimulation methodologies for the estimation of household attributes. The Fourth International Conference on GeoComputation, 25–28 July 1999, Fredericksburg, Virginia, USA (paper presentation); Ballas, D, Clarke, G. P., 2000. GIS and microsimulation for local labour market policy analysis. Computers, Environment and Urban Systems 24, 305–330; Ballas, D., Clarke, G. P., 2001a. Modelling the local impacts of national social policies: a spatial microsimulation approach. Environment and Planning C: Government and Policy 19, 587–606; Ballas, D., Clarke, G. P., 2001b. Towards local implications of major job transformations in the city: a spatial microsimulation approach. Geographical Analysis 33, 291–311]. It describes the development of the simulation model for the Irish local economy (SMILE) model. SMILE is a static and dynamic spatial microsimulation designed to analyse the impact of policy change and economic development on rural areas in Ireland. This paper focuses on the static model. First, we describe the European and Irish policy environment and indicate the importance of building spatial models to analyse change in rural Ireland. Second, we review existing literature on regional and local modelling techniques and the use of spatial models as tools for policy analysis. Third, we describe the SMILE static model. The model generates synthetic spatially referenced population for the Irish Republic at the small area level—the population micro data is produced for district electoral divisions (DEDs). Finally, we show how data from other sources can be linked to the static model output. We link data from the Irish National Farm Survey on farm system, income and off-farm employment of operator to the SMILE static model. We use this example to show its potential as a tool for policy analysis.

Support System for Trading in Exchange Market by Distributional Forecasting Model

A lot of work is devoted to formalizing and devising architectures for agents' cooperative behaviour, for coordinating the behaviour of individual agents within groups, as well as to designing agent societies using social laws. However, providing agents with abilities to automatically devise societies so as to form coherent emergent groups that coordinate their behaviour via social laws, is highly challenging. These systems are called self-organised. We are beginning to understand some of the ways in which self-organised agent systems can be devised. In this perspective, this paper provides several examples of multi-agent systems in which self-organisation, based on different mechanisms, is used to solve complex problems. Several criteria for comparison of self-organisation between the different applications are provided.

Temporal Development Methods for Agent-Based

In this paper we overview one specific approach to the formal development of multi-agent systems. This approach is based on the use of temporal logics to represent both the behaviour of individual agents, and the macro-level behaviour of multi-agent systems. We describe how formal specification, verification and refinement can all be developed using this temporal basis, and how implementation can be achieved by directly executing these formal representations. We also show how the basic framework can be extended in various ways to handle the representation and implementation of agents capable of more complex deliberation and reasoning.

Building a dynamic spatial microsimulation model for Ireland

Microsimulation describes economic and social events by modelling the behaviour of individual agents. These models have proved useful in evaluating the impact of policy changes at the micro-level. Spatial microsimulation models contain geographical information and allow for a regional or local approach to policy analysis. This paper builds on previous work on urban systems by employing similar modelling techniques for the analysis of rural areas. It describes the development of the SMILE (Simulation Model for the Irish Local Economy) model. SMILE is a dynamic spatial microsimulation model designed to analyse the impact of policy change and economic development on rural areas in Ireland. At its core, SMILE is a model of population. It simulates the basic components of population change, fertility, mortality and internal migration, at a small area level. This paper describes the method for projecting population change at the sub-county level. Results from the 1991 and 1996 dynamic model at county level are discussed, and a brief comparison is made with other methods. Finally, the features that distinguish microsimulation models from other population projection models are discussed. Copyright © 2005 John Wiley & Sons, Ltd.

Nanoeconomics

In 1987 K. Arrow suggested to define the theory of economic behavior of individual economic agents in market or nonmarket conditions as nanoeconomics. In 1996 we considered nanoeconomics for the first time as an independent branch of the economic theory and as a description of special condition of the Russian economy ("economy of physical persons"). In the given paper features of nanoeconomics in comparison with micro-, meso-, and macroeconomics are investigated, characteristics of the Russian economy essential from the nanoeconomic point of view are analyzed. It is shown that the stage of the "economy of physical persons" in the modified form still exists in Russia up to this day.

Elasticities of electricity demand in urban Indian households

In the past, several electricity demand studies have been published for India based on aggregate macro data at the country or sub-national/state level. Since the underlying theory of consumer demand is based on the behaviour of individual agents, the use of micro data, which reflects individual and household behaviour, more closely, can shed greater light on the nature of consumer responses. In this paper, seasonal price and income elasticities of electricity demand in the residential sector of all urban areas of India are estimated for the first time using disaggregate level survey data for about 30,000 households. Three electricity demand functions have been econometrically estimated using monthly data for the winter, monsoon and summer season in order to understand the extent to which factors like income, prices, household size and other household specific characteristics, influence variations observed in individual households’ electricity demand. The results show electricity demand is income and price inelastic in all three seasons, and that household, demographic and geographical variables are significant in determining electricity demand.

Micro versus Macro Acreage Response Models: Does Site-Specific Information Matter?

Because requisite micro data frequently are unavailable, it is common practice to use aggregate data to estimate economic relationships representing the behavior of individual agents. A substantial body of literature has examined conditions under which inferences between micro and aggregate specifications can be made. Less attention has been focused on the relative accuracy of predictions for each scale of model. In an empirical application, we compare the goodness-of-fit measures of eight sets of acreage response models, varying in aggregation from field- (micro-) level to regional- (macro-) level models. Results suggest aggregate models are superior to the micro model in predicting acreage response, even though the micro models contain substantially more data on site-specific characteristics.

Adventures in Modeling

Shiny Happy Turtles? Adventures in Modeling: Exploring Complex, Dynamic Systems with StarLogo is a cleverly written and illustrated, comprehensive “StarLogo for dummies” manual. Any secondary school science teacher with a desire to bring technology into the classroom will regard this text as a rich source of ideas. StarLogo software provides a multipurpose teaching medium through which a teacher can illustrate the process of science investigation, the predictive nature of models, and the difficult-to-grasp concept of complex systems. What sets StarLogo apart from other modeling software is that the behavior of individual agents is manipulated, which allows students to observe complex behaviors resulting from a series of simple behaviors. Users are given the opportunity to investigate the effect individuals have on the environment as well as environmental influence on the behavior of individuals (individuals are referred to as “turtles”). The typical secondary school science experience often fails to provide students with opportunities to learn about the very nature of science; we are graduating seniors who are not quite sure what the phrase, “science as a way of knowing” really means. Why has it been so difficult to infuse technology and inquiry-based learning into science classes? One of the many roadblocks is the paucity of quality, teacher-friendly, fieldtested lessons and reassurance that the lessons can simultaneously satisfy the standardsbased requirements of an already over-stuffed curriculum. Adventures in Modeling offers a long-awaited infusion. This manual emerges from the talents of Stevens Colella and Klopfer, who provide expertise in the role of innovative computational tools in the teaching and learning process, and the effectiveness of learning about complex phenomena through simulations. They jointly conduct secondary school StarLogo workshops at the Santa Fe Institute and MIT. Resnick is, of course, the visionary who developed the original StarLogo modeling software. The paperback describes the notion of decentralized systems, the StarLogo approach to modeling systems along with the importance of models in science and education, and ideas to connect Adventures projects with state and national standards. Sample projects (on an enclosed CD and on the MIT Media Laboratory website) model concepts such as diffusion, probability, natural selection, species interactions, and demographics, all of which satisfy state and national standards for science as well as social studies, statistics, and mathematics.

Continuum time limit and stationary states of the minority game

We discuss in detail the derivation of stochastic differential equations for the continuum time limit of the minority game. We show that all properties of the minority game can be understood by a careful theoretical analysis of such equations. In particular, (i) we confirm that the stationary state properties are given by the ground state configurations of a disordered (soft) spin system, (ii) we derive the full stationary state distribution, (iii) we characterize the dependence on initial conditions in the symmetric phase, and (iv) we clarify the behavior of the system as a function of the learning rate. This leaves us with a complete and coherent picture of the collective behavior of the minority game. Strikingly we find that the temperaturelike parameter, which is introduced in the choice behavior of individual agents turns out to play the role, at the collective level, of the inverse of a thermodynamic temperature.

Collective effects from induced behaviour

We present a solvable model for describing quantitatively situations where the individual behaviour of agents in a group "percolates" to collective behaviour of the group as a whole as a result of mutual influence between the agents.

Cognitive Engineering Challenges of Managing Swarms of Self-Organizing Agent-Based Automation

Function allocation, mode errors, and misuse of automation have become increasingly important research topics as technology has become more sophisticated. These and related problems will emerge as critical research issues as self-organizing, agent-based automation becomes more prominent. While current research has studied how people control a small number (2 to 10) of agents, the future will likely introduce the challenge of supervising hundreds of agents. Complex automation that is built from hundreds of loosely connected intelligent agents may exhibit powerful new adaptive behaviors. This emergent behavior may not be an intuitive extension of individual agent behavior. Addressing the challenge of this new technology will require a theoretical understanding of human behavior that goes beyond a task-based description of well-defined scenarios. Several important research questions include: What is the best way to support effective management of the agents? How can potential problems among the agents be identified and predicted? What display concepts are most effective for controlling large numbers of agents? How can the emergent agent behavior constrained so that it is comprehensible to human operators?

A note on the individualistic foundations of the core in economies with asymmetric information

Two foundations of the core are considered in the context of exchange economies: the standard coalition based interpretation, and one based on the individual profit seeking behaviour of agents. The resulting core notions coincide in symmetric information economies but diverge when generalized to economies with asymmetric information.