Publications referencing Swarm

[Luna:Perrone:2001] Agent-Based Methods in Economics and Finance: Simulations in Swarm. Francesco Luna and Alessandro Perrone. 0-7923-7419-3. Kluwer Academic Publishers. October 2001.
Series: Advances in Computational Economics. volume 17. Hans Amman and Anna Nagurney.

Abstract: Extract of book description from the publishers:

This volume on financial and economic simulations in Swarm marks the continued progress by a group of researchers to incorporate agent-based computer models as an important tool within their discipline.

Swarm promotes agent-based computer models as a tool for the study of complex systems. A common language is leading to the growth of user communities in specific areas of application. Furthermore, by providing an organizing framework to guide the development of more problem-specific structures, and by dealing with a whole range of issues that affect their fundamental correctness and their ability to be developed and reused, Swarm has sought to make the use of agent-based models a legitimate tool of scientific investigation that also meets the practical needs of investigators within a community....

[Luna:Stefansson:2000] Economic Simulations in Swarm: Agent-Based Modelling and Object Oriented Programming. Francesco Luna and Benedikt Stefannson. 0-7923-8665-5. Kluwer Academic Publishers. 2000.
Series: Advances in Computational Economics. volume 14. Hans Amman and Anna Nagurney.

Abstract: Book description from the publishers:

Computer simulations of economic systems are slowly gaining ground within the economic profession. However, such a process is hindered by a lack of communication among researchers who do not share a common language. For its object-oriented structure and its versatility, Swarm has the necessary characteristics to become a credible universal language of agent-based simulations. Economic Simulations in Swarm collects a series of original articles in such domains as macro and micro economics, industrial organization, monetary theory, and finance, all linked by a common denominator: the use of the Swarm simulation platform.

Swarm, a standard set of program libraries, allows users to construct simulations where a collection of heterogeneous independent agents or elements interact through discrete events. This volume offers the first extensive tutorial to the use of these software libraries developed at the Santa Fe Institute as part of the ongoing research into complexity.

The editors conceived the idea of this book while visiting the Santa Fe Institute as members of the `Working Group on Adaptive and Computable Economics'. Francesco Luna is a specialist in Computable Economics, and Benedikt Stefansson is an active contributor to the Swarm community.

An outline of the book and source code for models discussed in the book are available here.

[Armstrong:1998] Aaron A. Armstrong and Edmund H. Durfee . " Mixing and Memory: Emergent Cooperation in an Information Marketplace "Proceedings of the Third International Conference on Multiagent SystemsJuly 1998. . IEEE Computer Society Press .

[Booth:1997] Ginger Booth . "Gecko: A Continuous 2D World for Ecological Modeling"Artificial Life. 3. 3. 147--163. Summer 1997.

[Bruhn:1997] Peter Bruhn . Master's Thesis. Enterprise Simulation using Multi-Agent System Modeling and the Swarm Toolkit . October 1997.

[Burkhart:1994] Roger Burkhart . "The Swarm Multi-Agent Simulation System"(OOPSLA) '94 Workshop on "The Object Engine"7 September 1994. .

[Burkhart:1995] Roger Burkhart . Object-Oriented Programming Systems, Languages, and Applications (OOPSLA) '95 Adaptable and Adaptive Software Workshop8 October 1995. . " Create-phase Protocols for Object Customization"

[Burkhart:1997] Roger Burkhart . "Schedules of Activity in the Swarm Simulation System"OOSPLA '97 Workshop on OO Behavioral Semantics1997. .

[Carnahan:1997] John Carnahan , Song-gang Li , Carlo Costantini , Yeya T. Toure , and Charles E. Taylor . MIT Press . " Computer Simulation of Dispersal by em Anopheles Gambiae s.l. in West Africa "Artificial Life V: Proceedings of the Fifth International Workshop on the Synthesis and Simulation of Living Systems1997. . 387--394 .
Series: Complex Adaptive Systems. MIT Press. Boston.

[Chantemargue:1998a] F. Chantemargue , T. Dagaeff , M. Schumacher , and B. Hirsbrunner . " Autonomous Agents and Cooperation: Application to Collective Robotics "University of Fribourg. Computer Science Department. Fribourg Switzerland. . Internal Note 98-03. February 1998.

[Chantemargue:1998b] F. Chantemargue , O. Krone , M. Schumacher , T. Dagaeff , and B. Hirsbrunner . " Autonomous Agents: from Concepts to Implementation "Proceedings of the Fourteenth European Meeting on Cybernetics and Systems Research (EMCSR'98)April 14-17 1998. ViennaAustria. . 731--736 . 2 . 1998 .

[Cohen:1999] Michael D. Cohen , Rick L. Riolo , and Robert Axelrod . "The Emergence of Social Organization in the Prisoners' Dilemma: How Context-Preservation and other Factors Promote Cooperation"PSCS Working Paper 99-01-002. January 1999.

[Coyle:2001] Demonstrating Darwinian Evolution Using Swarm. Lorcan Coyle. May 2001.

Abstract: This report details the design and implementation of an artificial world that demonstrates Darwinian evolution. This is done using an agent based modellingtool called Swarm. This world is populated with hundreds of agents that compete with one another to survive. Their behavioural attributes are coded into their genes. The initial population consists of individuals with randomly coded genes. It is hoped that by exerting Darwinian evolution on this, a population of agents, optimally suited for survival in the world will emerge.

[Dagaeff:1997] T. Dagaeff , F. Chantemargue , and B. Hirsbrunner . Proceedings of the Second European Conference on Cognitive Science (ECCS'97) Manchester U.K. . April 9-11. . 91-96 . "Emergence-based Cooperation in a Multi-Agent System" 1997 .

[Downing:1999] Keith Downing and Peter Zvirinsky . "The Simulated Evolution of Biochemical Guilds: Reconciling Gaia Theory and Natural Selection"Artificial Life. 5. 4. 2000.

Abstract: Gaia theory, which states that organisms both affect and regulate their environment, poses an interesting problem to Neo-Darwinian evolutionary biologists and provides an exciting set of phenomena for artificial-life investigation. The key challenge is to explain the emergence of biotic communities that are capable, via their implicit coordination, of regulating large-scale biogeochemical factors such as the temperature and chemical composition of the biosphere, but to assume no evolutionary mechanisms beyond contemporary natural selection. Along with providing an introduction to Gaia theory, this paper presents simulations of Gaian emergence based on an artificial-life model involving genetic algorithms and guilds of simple metabolizing agents. In these simulations, resource competition leads to guild diversity; the ensemble of guilds then manifests life-sustaining nutrient recycling and exerts distributed control over environmental nutrient ratios. These results illustrate that standard individual-based natural selection is sufficient to explain Gaian self-organization, and they help clarify the relationships between two key metrics of Gaian activity: recycling and regulation.

[Fulkerson:1997] B. Fulkerson and G. Staffend . " Decentralized Control in the Customer Focused Enterprise "Annals of Operations Research. 325--333 . 77 . 1997 .

Abstract: This paper discusses analytical methods to enable the order fulfillment process (OFF) of a customer-focused enterprise. We present three examples of agent-based systems that illustrate the benefits of decentralized control in discrete part manufacturing. The Swarm simulation platform is introduced as a novel means to investigate supply chain management strategies.

[Hinsch:1998] M. Hinsch and J. J. Merelo . "Coevolving Iterated Prisonner's dilemma strategies in different environments"Univ. Granada, Spain. GeNeura Team, Dept. ATC,. . g-98-1. 1998 .

[Jares:1998] Tim Jares . The Survival and Consequences of Noise Traders in Financial Markets: A Numerical Modeling Approach . PhD Thesis. University of Nebraska. . August 1998.

[Johnson:1998a] Paul Johnson . " Adaptive Agents versus Rational Actors: Social Science Implications "Annual Meeting of the American Political Science Association3-6 September 1998. Marriott Copley Place and Sheraton Boston Hotel and TowerBoston . .

[Johnson:1998b] Paul Johnson . " An Agent Based Model of the Exchange Theory of Interest Groups "Annual Meeting of the American Political Science Association3-6 September 1998. Marriott Copley Place and Sheraton Boston Hotel and TowerBoston. .

[Kohler:1996a] T.A. Kohler and Eric Carr . " Swarm-based Modeling of Prehistoric Settlement Systems in Southwestern North America"Proceedings of Colloquium II, UISPP, XIIIth CongressSeptember 1996. .
Series: Sydney University Archaeological Methods. 5. I. Johnson and M. North. School of Archaeology, University of Sydney, Australia .

[Kohler:1996b] T. A. Kohler , Carla R. Van West , Eric P. Carr , and Christopher G. Langton . "Agent-Based Modeling of Prehistoric Settlement Systems in the Northern American Southwest"Proceedings of Third International Conference Integrating GIS and Environmental Modeling, Santa Fe, New Mexico1996. . National Center for Geographic Information and Analysis. Santa Barbara.

[Kohler:1999] T. A. Kohler , J. Kresl , C. Van West , Eric Carr , and Richard Wilshusen . "Be There Then: A Modeling Approach to Settlement Determinants and Spatial Efficiency among late Ancestral Pueblo Populations of the Mesa Verde Region, U.S. Southwest"Dynamics in Human and Primate Societies: Agent-Based Modeling of Social and Spatial Processes. Timothy Kohler and George Gumerman. Santa Fe Institute and Oxford University Press . 1999 .

[Kreft:1998] Jan-Ulrich Kreft , Ginger Booth , and Julian W. T. Wimpenny . "BacSim, a simulator for individual-based modelling of bacterial colony growth"Microbiology. 3275 - 3287. 144 . 1998 .

[Krone:1998a] O. Krone , F. Chantemargue , T. Dagaeff , M. Schumacher , and B. Hirsbrunner . 149-158 . " Coordinating Autonomous Entities "Proceedings of the ACM Symposium on Applied Computing (SAC'98). Special Track on Coordination, Languages and ApplicationsFebruary 27 - March 1 1998. AtlantaGeorgiaUSA. .

[Krone:1998b] O. Krone , F. Chantemargue , T. Dagaeff , and M. Schumacher . " Coordinating Autonomous Entities with STL "The Applied Computing Review. Special issue on Coordination Models Languages and Applications. 1998 (to appear).

[Krothapalli:1997] N.K.C. Krothapalli and A. V. Deshmukh . " Effects of negotiation mechanisms on performance of agent based manufacturing Systems "Proceedings of the Seventh International Conference on Flexible Automation and Intelligent Manufacturing1997. . 704-717 .

Abstract: This paper proposes new inter-agent negotiation mechanisms for improving the performance of agent based or decentralized manufacturing systems. The focus of this paper is on demonstrating efficiency of different negotiation and collaboration schemes between agents of the same class (parts, machines, etc) and inter-class negotiations using currency metrics. The cooperation and negotiation protocols are modeled using the em Swarm multi-agent simulation platform. We demonstrate the robustness of the proposed schemes, and compare them with hierarchical scheduling systems.

[Krothapalli:1998a] N.K.C. Krothapalli and A. V. Deshmukh . " Self-regulating negotiating schemes for robust agent--based manufacturing systems "Proceedings of the Seventh Industrial Engineering Research Conference1998. .

Abstract: Agent-based manufacturing systems offer several advantages over hierarchically organized systems. However, performance of agent-based systems has been a major concern which has hampered widespread acceptance of these systems. Several researchers have noted that the performance of agent-based systems is highly sensitive to the bidding or negotiation protocols used. In this paper, we study the robustness of system performance measures with respect to the negotiation protocols used by the individual agents. We propose self-regulating negotiation schemes which prevent the agents from ``price'' or ``utility'' cascades. The core of the self-regulatory mechanism lies in a dynamic utility curve, which is based on the current state and the past history of the agent.

[Krothapalli:1998b] N.K.C. Krothapalli and A.V. Deshmukh . " Design of negotiation protocols for multi--agent manufacturing systems "International Journal of Production Research. 1998 (in press).

Abstract: This paper proposes new inter-agent and intra-agent negotiation mechanisms for improving the performance of multi-agent or decentralized manufacturing systems. The overall performance of this system depends on the effective interactions between agents. This research presents methods which would permit cooperation and multi--stage interactions among agents. Agents may collaborate or preempt other agents based on the available currency and task criticality. The objective of this research is to demonstrate the efficiency of different negotiation and collaboration schemes between agents of the same class (parts, machines, etc), and inter-class negotiations using currency metrics and preemption. The proposed negotiation schemes are implemented using the Swarm simulation platform.

[Manuca:1998] Radu Manuca , Yi Li , Rick Riolo , and Robert Savit . "The Structure of Adaptive Competition in Minority Games"PSCS Working Paper98-11-001. 1998.

[Marshall:1999] J.A.R. Marshall and J.E. Rowe . "The Evolution of Cooperation Through Kin Selection "International Journal of Systems Science. 1999 (submitted).

[McMullin:1997a] Barry McMullin .

Abstract: This report presents a detailed review and re-presentation of the algorithm for (computational) realisation of autopoiesis, originally presented by Varela et al. (1974). The review is from the perspective of one seeking to re-implement this algorithm. It arises from an on-going project to develop such a re-implementation using the Swarm simulation system.[1] The motivation for such re-implementation is firstly to critically re-examine the phenomenology generated by this model chemistry, and secondly to use it as a basis for exploring more complex systems. The algorithm is first reviewed and annotated for internal consistency and clarity; it is then separately reviewed for consistency with the experimental results which originally accompanied it. A number of significant discrepancies are discussed. By kind permission of Francisco Varela, this report also includes, as an Appendix, some previously unpublished documentation and source code (in FORTRAN IV) associated with the original model. By critical consideration of the experimental results in conjunction with this code, an important--perhaps crucial--interaction, not included in any previous description of the model, has been re-discovered. This interaction is presented and discussed briefly.

[McMullin:1997b] Barry McMullin . "SCL: An Artificial Chemistry in Swarm"SFI Working Paper 97-01-002. January 1997.

Abstract: This report describes the SCL (v0.04) system. This is an implementation of an artificial chemistry, using the Swarm simulation system. This chemistry is qualitatively based on the system first described in Varela et al. (1974). This involves three distinct chemical species: Substrate, Catalyst and Link, hence SCL. It was designed with a view to generating simple phenomena of autopoietic organisation. Varela et al. included a detailed algorithmic account of their original model; however, as documented in (McMullin 1997), there are a number of problems with interpreting and/or re-implementing that algorithm. Arising from this, that original algorithm was essentially set aside in designing SCL; instead, SCL seeks to capture only the general, qualitative, reaction schemes described by Varela et al. SCL was developed for two separate purposes. Firstly, it provides a platform to critically re-evaluate the phenomena--particularly autopoietic phenomena--that can be realised with this general kind of reaction scheme. That phenomenological investigation will be described in a separate report. The second objective was to gain experience of the Swarm simulation system and evaluate its suitability for this kind of project. This report is concerned solely with this second objective: i.e. with documenting the implementation, and with evaluating the use of Swarm.

[McMullin:Varela:1997] Barry McMullin and Francisco J. Varela . "Rediscovering Computational Autopoiesis"Proceedings of the Fourth European Conference on Artificial LifeJuly 1997. School of Cognitive and Computing Sciences, University of Sussex. .
Series: Complex Adaptive Systems. Phil Husbands and Inman Harvey. MIT Press .

Abstract: This paper summarises some initial empirical results from a new computer model (artificial chemistry) which exhibits spontaneous emergence and persistence of autopoietic organisation. The model is based on a system originally presented by Varela, Maturana and Uribe. In carrying out this re-implementation it was found that an additional interaction (chain-based bond inhibition), not documented in the original description by Varela et al., is critical to the realisation of the autopoietic phenomena. This required interaction was re-discovered only following careful examination of (unpublished) source code for an early version of the original model. The purpose of the paper is thus twofold: firstly to identify and discuss this previously undocumented, but essential, interaction; and secondly to argue, on the basis of this particular case, for the importance of exploiting the emerging technologies which support publication of completely detailed software models (in addition, of course, to conventional publication of summary experimental results).

[Minar:1996] Nelson Minar , Rogert Burkhart , Chris Langton , and Manor Askenazi . "The Swarm Simulation System: A Toolkit for Building Multi-Agent Simulations"SFI Working Paper 96-06-042. 1996 .

Abstract: Swarm is a multi-agent software platform for the simulation of complex adaptive systems. In the Swarm system the basic unit of simulation is the swarm, a collection of agents executing a schedule of actions. Swarm supports hierarchical modeling approaches whereby agents can be composed of swarms of other agents in nested structures. Swarm provides object oriented libraries of reusable components for building models and analyzing, displaying, and controlling experiments on those models. Swarm is currently available as a beta version in full, free source code form. It requires the GNU C Compiler, Unix, and X Windows. More information about Swarm can be obtained from our web pages http://www.swarm.org

[Parunak:1998] H. V. D. Parunak , R. Savit , and R. L. Riolo .
Series: LNAI series. 1534. Sichman, Conte, and Gilbert. Multi-agent systems and Agent-based Simulation (MABS'98)1998. . Springer-Verlag. " Agent-Based Modeling vs. Equation-Based Modeling: A Case Study and Users' Guide " 1998 .

[Pepper:1999] J.W. Pepper and B. Smuts . "The evolution of cooperation in an ecological context: an agent-based model"Dynamics in Human and Primate Societies: Agent-Based Modeling of Social and Spatial Processes. Timothy Kohler and George Gumerman. Santa Fe Institute and Oxford University Press . 1999 .

[Pepper:2000] John Pepper. "The evolution of modularity in genome architecture"Evolvability workshop at Artificial Life VII1-2 August 2000. Reed College Portland Oregeon . .

[Polhill:2001] Imitative versus nonimitative strategies in a land-use simulation. J. G. Polhill, N. M. Gotts, and A. N. R. Law. 2001. Cybernetics and Systems. 32. 1-2. 285-307.

Abstract: This article describes results from a simulation model of rural land use, focusing on how the relative advantages of imitative and nonimitative approaches to land use selection change under different circumstances. It is shown that the success of "imitation" depends in quite complex ways on the type of imitation used, the strategies of other agents with which the imitator is interacting, and aspects of the heterogeneity of the environment.

[Railback:1999b] S. F. Railsback, R. H. Lamberson, and S. Jackson. "Individual-based Models: Progress Toward Viability for Fisheries Management"Spatial Processes and Management of Fish Populations, Proceedings of the 17th Lowell Wakefield SymposiumAnchorageAlaska. . 1999 (submitted).

Abstract: Individual-based models have many features desirable for fisheries management: they are the only class of models that can easily represent many natural complexities, spatial processes, and cumulative effects; and their individual orientation makes them easy to understand and parameterize with laboratory and field observations. However, these models are currently viewed as impractical because of complexity and cost, and they lack scientific and regulatory credibility. We have a program to overcome these obstacles by developing new theoretical approaches and software. Theoretical development has focused on improving and testing the rules that govern fish movement, because movement is the primary way fish respond to spatial processes. We let each fish select habitat that maximizes a simple definition of fitness that is based on the expected probability of surviving starvation and other risks over a future time horizon. We also developed software with graphical interfaces allowing the behavior of individual fish to be observed and tested, a prerequisite for establishing the credibility of individual-based models.

[Railsback:1999a] S. F. Railsback , R. H. Lamberson , B. C. Harvey , and W. E. Duffy . "Movement rules for individual-based models of stream fish"Ecological Modelling. 2-3. 123. 73-89. 1999.

Abstract: Spatially explicit individual-based models use movement rules to determine when an animal departs its current location and to determine its movement destination; these rules are therefore critical to accurate simulations. Movement rules typically define some measure of how an individual's expected fitness varies among locations, under the assumption that animals make movement decisions at least in part to increase their fitness. Recent research shows that many fish move quickly in response to changes in physical and biological conditions, so movement rules should allow fish to rapidly select the best location that is available and accessible and not impose randomness or time lags on movement. The theory that a fish's fitness is maximized by minimizing the ratio of mortality risk to food intake is not applicable to typical individual-based model movement decisions and can cause serious errors in common situations. Instead, we developed fitness measures from unified foraging theory that are theoretically and computationally compatible with individual-based fish models. One such fitness measure causes a fish to select habitat that maximizes its expected survival over a specified time horizon, considering both starvation and non-starvation risks. This fitness measure is dependent on the fish's current state, making fish with low energy reserves more willing to accept risks in exchange for higher intake. A second measure represents expected reproductive maturity by multiplying expected survival by a factor representing how close to the size of first reproduction the fish grows within the time horizon.

[Railsback:1999c] Lang, Railsback & Assoc.. "Tools for Individual-based Stream Fish Models: Improving the Cost-Effectiveness and Credibility of Individual-based Approaches for Instream Flow Assessment"EPRI, Electric Power Research Institute, Palo Alto, CA. EPRI TR-114006. 1999.

[Railsback:2000a] S. F. Railsback and B. C. Harvey. Individual-based Model Formulation for Cutthroat Trout, Little Jones Creek, California. U.S. Forest Service, Redwood Sciences Laboratory, Arcata, CA.. (in preparation).

[Railsback:2000b] S. F. Railsback and B. C. Harvey. "Comparison of salmonid habitat selection objectives in an individual-based model"Ecology. January 2000 (in preparation).

[Satterfield:1999] T. Satterfield and M. Murphy . " A computational model of creole genesis "Linguistic Society of America MeetingJanuary 1999. Los Angeles. .

[Savage:1998] Melissa Savage and Manor Askenazi . "Arborscapes: A Swarm-Based Multi-agent Ecological Disturbance Model"Submitted, available as SFI Working Paper 98-06-056. Geographical and Environmental Modelling. 1998 .

Abstract: This paper presents an agent-based, object-oriented ecological model of forest dynamics designed to examine the role of disturbance on diversity. Arborscapes is based on Swarm, an agent-based software platform that offers advantages for ecological modeling, including a suite of standardized libraries of objects, schedules, and probes, and architectural features such as inheritance, message passing, encapsulation, and hierarchical structure. Object-oriented models are more transparent, portable and more easily modified than process oriented models, and therefore promise to facilitate collaboration on computational experiments. The initial application of Arborscapes was the analysis of disturbance dynamics, but the model was designed to be modified for a variety of applications in the simulation of vegetation community dynamics.

[Savage:2000] Melissa Savage, Bruce Sawhill, and Manor Askenazi. "Community Dynamics: What Happens When We Rerun the Tape?"Journal of Theoretical Biology. 515-526. 205. 4. 2000.

[Savit:1997] Robert Savit , Radu Manuca , and Rick Riolo . "Adaptive Competition, Market Efficiency, Phase Transitions and Spin-Glasses"LANL Eprint archives paper adap-org/9712006. 1998 .

[Savit:1998] Robert Savit , Radu Manuca , and Rick Riolo . "The Dynamics of Minority competition"Physical Review Letters. 1998.

[Schretzenmayr:1998] Martina Schretzenmayr . Strategien zur Umnutzung von grossflaechigen innerstaedtischen Industrie- und Gewerbebrachen (Strategies for the redevelopment of large-scale inner city industrial sites) . PhD Thesis, ETH No. 12473, in German. 1998 .

Abstract: This work examines the redevelopment of large-scale inner city brownfield sites using case studies of five German and two Swiss sites. Special emphasis is placed on the suitability of different planning strategies for redeveloping brownfield sites. It could be shown, that the control mechanism of stage-wise planning, which is normally used for the development of greenfield sites, becomes ineffective for brownfield sites because every parcel of an industrial or commercial site is available for immediate redevelopment Despite the inadequacies of stage-wise planning, this approach was the most commonly observed in the case studies. The examination of the case study sites has revealed that the redevelopment of industrial sites tends to be concentrated around the edges of the sites and also around parcels which are made especially attractive by their accessibility to transportation (e.g. near subway stations). Furthermore, parcels near so-called "facilities with surplus importance" are preferred. "Facilities with surplus importance" refer to those facilities which can serve as seeds for the attachment of facilities with similar or associated uses (multiplier effect). Examples include technology transfer facilities or recreational and cultural facilities which might encourage the development of nearby hotels and restaurants. A hypothesis formulated at the beginning of this work proved to be appropriate for the redevelopment of brownfield sites. This strategy aims to establish "facilities of surplus importance" at suitable locations in the interior of the site. These points will then serve as "condensation nuclei". The "condensation nuclei" should be placed at intersections of public and private transportation links in order to exploit available access routes. Public transportation, especially rail transport, should have high priority as an investment for the future of the site. The redevelopment process will be initiated at the "condensation nuclei" and will grow from these to cover the whole site. Placing such "condensation nuclei" adjacent to traffic intersections guarantees access to new buildings and facilities and ensures that new modes of public transportation will be fully utilized - even in the very beginning of the redevelopment process. The proposed strategy has been tested using a multi-agent simulation of complex systems (Swarm) and could be verified. Finally, after analyzingq the planning process of the surveyed case studies, this work formulates recommendations for the execution of redevelopment projects.

[Stefansson:1997] B. Stefansson . " Swarm: An Object Oriented Simulation Platform Applied to Markets and Organizations "Evolutionary Programming VI1997. .
Series: Lecture Notes in Computer Science. 1213. P. Angeline, R. Reynolds, J. McDonnel, and R. Eberhart. Springer-Verlag . New York.

[Strader:1998] Troy J. Strader , Fu-Ren Lin , and Michael J. Shaw . "Simulation of Order Fulfillment in Divergent Assembly Supply Chains"Journal of Artificial Societies and Social Simulation. 1 . 2. March 1998.

Abstract: Management of supply chains is a difficult task involving coordination and decision-making across organizational boundaries. Computational modeling using multi-agent simulation is a tool that can provide decision support for supply chain managers. We identify the components of a supply chain model and implement it in the Swarm multi-agent simulation platform. The model is used to study the impact of information sharing on order fulfillment in divergent assembly supply chains (commonly associated with the computer and electronics industries). We find that efficient information sharing enables inventory costs to be reduced while maintaining acceptable order fulfillment cycle times. This is true because information, which provides the basis for enhanced coordination and reduced uncertainty, can substitute for inventory.

[Strader:1999] Troy J. Strader , Fu-Ren Lin , and Michael J. Shaw . " The Impact of Information Sharing on Order Fulfillment in Divergent Differentiation Supply Chain "Journal of Global Information Management. 7 . 1. January - March 1999.

[Terna:1998a] P. Terna .

Abstract: Social scientists are not computer scientists, but their skills in the field have to become better and better to cope with the growing field of social simulation and agent based modelling techniques. A way to reduce the weight of software development is to employ generalised agent development tools, accepting both the boundaries necessarily existing in the various packages and the subtle and dangerous differences existing in the concept of agent in computer science, artificial intelligence and social sciences. The choice of tools based on the object oriented paradigm that offer libraries of functions and graphic widgets is a good compromise. A product with this kind of capability is Swarm, developed at the Santa Fe Institute and freely available, under the terms of the GNU license. A small example of a model developed in Swarm is introduced, in order to show directly the possibilities arising from the use of these techniques, both as software libraries and methodological guidelines. With simple agents - interacting in a Swarm context to solve both memory and time simulation problems - we observe the emergence of chaotic sequences of transaction prices.

[Terna:1998b] P. Terna . "ABCDE: Agent Based Chaotic Dynamic Emergence"
Series: Lecture Notes in Artificial Intelligence. 1534. Multi-Agent Systems and Agent-Based Simulation, First International Workshop, MABS'98. Springer . Berlin. 1998.

Abstract: This paper concerns agent based experiments in the field of negotiation and exchange simulation. A computer simulation environment is built, showing the emergence of chaotic price sequences in a simple model of interacting consumers and vendors, both equipped with minimal rules. em Swarm the framework of the model (www.santafe.edu/projects/swarm), a simulation tool with a strong object oriented structure, also very useful to separate in a clear way the model level from the level of the observer. Swarm is fully programmable in Objective C, with many powerful libraries, aimed at modeling the objects and the schedules of our experiments, with lists and arrays where necessary. Finally we introduce a tool (Cross Target method: CT), useful in building artificial laboratories, for experiments with learning, self-developed consistency and interaction of agents in artificial worlds, in order to observe the emergence of complexity without a priori behavioral rules: The perspective of our work is that of developing CT within the Swarm framework to replicate the ABCDE experiment in this light-rules or no-rules context.

[Terna:2000c] P. Terna. "Economic Experiments with Swarm: a Neural Network Approach to the Self-Development of Consistency in Agents' Behavior"Economic Simulations in Swarm: Agent-Based Modelling and Object Oriented Programming. F. Luna and B. Stefansson. Dordrecht and London, Kluwer Academic. 2000.

Abstract: We underline the usefulness of agent based models in the social science perspective, also focusing on the main computational problems due to the structure of our models: to simplify the task we introduce a generalized Environment-Rules-Agents scheme. Finally, within Swarm, we introduce a neural network tool (Cross Target method), useful in building artificial laboratories, for experiments with learning, self-developed consistency and interaction of agents in artificial worlds, in order to observe the emergence of complexity without a priori behavioral rules.

[Terna:2000d] P. Terna. "The "mind or no mind" dilemma in agents behaving in a market"Applications of Simulation to Social Sciences. G. Ballot and G. Weisbuch. Paris, Hermes Science Publications. 2000.

Abstract: In computer simulation models based upon agents, what is the degree of sophistication that we have to put into the agents? Should we provide them or not with a "mind"? The answer ranges from Axelrod's simplicity principle to the use of full BDI (Beliefs, Intentions, Desires) cognitive agents. To discuss the subject we introduce here three models: one with "no-mind" agents that operate in an unstructured market, the second with "minded" agents assuring some stability to an emerging unstructured market and, finally, the third with no mind agents, that show a sophisticated outcome in a structured market. No generalised results come from this presentation, but many useful doubts.

[Villa:1998] F. Villa and R. Costanza . "Design of multi-paradigm integrating modeling tools for ecological research "Journal of Environmental Modelling and Software. multi-paradigm ecological modelling, remote simulation control, simulation interface design, model coordination, Swarm. 1998 (submitted).