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1.
Guido Fioretti 《Computational & Mathematical Organization Theory》2007,13(1):1-16
Organizational learning can be understood as a spontaneous development of routines. Mathematically, this process can be described as a search for better paths on a graph whose nodes are humans and machines. Since the rules for connecting nodes depend on their ability to process goods, the slope of the learning curve may be connected to physical and psychological properties. Two suggestive examples are discussed.
Guido Fioretti, born 1964, graduated in Electronic Engineering and obtained a PhD in Economics from the University of Rome “La Sapienza”. He is currently an assistant professor at the University of Bologna, Italy.His research interests span from decision theory to economics and organization science. In particular, he is interested in linking structural development to cognitive processes. The present article has been conceived as a theoretical underpinning of agent-based simulations of organizations. In particular, future applications of the Java Enterprise Simulator () may test the usefulness of the results derived herein. 相似文献
2.
Christian von Scheve Daniel Moldt Julia Fix Rolf von Luede 《Computational & Mathematical Organization Theory》2006,12(2-3):81-100
This contribution investigates the function of emotion in relation to norms, both in natural and artificial societies. We
illustrate that unintentional behavior can be normative and socially functional at the same time, thereby highlighting the
role of emotion. Conceiving of norms as mental objects we then examine the role of emotion in maintaining and enforcing such
propositional attitudes. The findings are subsequently related to social structural dynamics and questions concerning micro-macro
linkage, in natural societies as well as in artificial systems. Finally, we outline the possibilities of an application to
the socionic multi-agent architecture SONAR.
Christian von Scheve graduated in Sociology with minors in Psychology, Economics, and Political Science at the University of Hamburg, where he
also worked as a research assistant at the Institute of Sociology. Currently, he is a 3rd year PhD student at the University
of Hamburg. He was a Fellow of the Research Group “Emotions as Bio-Cultural Processes” at the Center for Interdisciplinary
Research (ZiF) at Bielefeld University. In his doctoral thesis he develops an interdisciplinary approach to emotion and social
structural dynamics, integrating emotion theories from the neurosciences, psychology, and the social sciences. He has published
on the role of emotion in large-scale social systems, human-computer interaction, and multi-agent systems. He is co-editor
of a forthcoming volume on emotion regulation.
Daniel Moldt received his BSc in Computer Science/Software Engineering from the University of Birmingham (England) in 1984, graduated
in Informatics at the University of Hamburg, with a minor in Economics in 1990. He received his PhD in Informatics from the
University of Hamburg in 1996, where he has been a researcher and lecturer at the Department of Informatics since 1990. Daniel
Moldt is also the head of the Laboratory for Agent-Oriented Systems (LAOS) of the theoretical foundations group at the Department
of Informatics. His research interests focus on theoretical foundations, software engineering and distributed systems with
an emphasis on agent technology, Petri nets, specification languages, intra- and inter-organizational application development,
Socionics and emotion in informatics.
Julia Fix is currently a PhD student at the Theoretical Foundations of Computer Science Group, Department for Informatics at the University
of Hamburg. She studied Informatics and Psychology at the University of Hamburg, with an emphasis on theoretical foundations
of multi-agent systems and wrote her diploma theses about emotional agent systems. Her current research interests focus on
conceptual challenges and theoretical foundations of modelling emotions in multi-agent systems, emotion-based norm enforcement
and maintenance, and Socionics. A further research focus are Petri nets, in particular the use of Petri-net modelling formalisms
for representing different aspects of emotion in agent systems.
Rolf von Lüde is a professor of Sociology at the University of Hamburg with a focus in teaching and research in Sociology of Organizations,
Work and Industry since 1996. He graduated in Economics, Sociology, and Psychology, and received his doctorate in Economics
and the venia legendi in Sociology from the University of Dortmund. His current research focuses on labor conditions, the
organization of production, social change and the educational system, the organizational structures of university, Socionics
as a new approach to distributed artificial intelligence in cooperation with computer scientists, new public management, and
emotions and social structures. Rolf von Lüde is currently Head of Department of Social Sciences and Vice Dean of the School
of Business, Economics and Social Sciences, University of Hamburg. 相似文献
3.
Paul Davidsson Stefan Johansson 《Computational & Mathematical Organization Theory》2006,12(2-3):169-180
Based on a classification of artificial societies and the identification of four different types of stakeholders in such societies,
we investigate the potential of norm-governed behavior in different types of artificial societies. The basis of the analysis
is the preferences of the stakeholders and how they influence the state of the society. A general conclusion drawn is that
the more open a society is the more it has to rely on agent owners and designers to achieve norm-governed behavior, whereas
in more closed societies the environment designers and owners may control the degree of norm-governed behavior.
Paul Davidsson is professor at the Department of Systems and Software Engineering, School of Engineering, Blekinge Institute of Technology,
Sweden. He received his Ph.D. in Computer Science in 1996 from Lund University, Sweden. His research interests include the
theory and application of multi-agent systems, autonomous agents, and machine learning. Application areas include logistics,
transport systems, district heating systems, building automation, and telecommunications systems. The results of this work
have been reported in more than 75 peer-reviewed scientific articles published in international journals and conference proceedings.
Moreover, he has been the co-editor of three books on Multi Agent Based Simulation and member of program committees of numerous
international conferences, such as the International Joint Conference on Autonomous Agents and Multi-Agent Systems
Stefan Johansson is an assistant professor at Department of Systems and Software Engineering, Blekinge Institute of Technology, Sweden, where
he also finished his PhD in 2002. The main research areas cover coordination issues in multi-agent systems and theories of
autonomous agents. Applications of special interests are agents in game ai, robotics, telecommunication networks. On his list
of publications are more than 35 peer-reviewed papers published in conference proceedings and scientific journals in the areas
of agents, ai, robotics and games. He has also been a member of a variety of programme committees of scientific conferences,
including e.g. Intelligent Agent Technology. 相似文献
4.
Edward B. Barbier 《Natural Resource Modeling》1992,6(4):451-453
Ecological Economics: The Science and Management and Sustainability, Robert Costanza, Editor, Columbia University Press, New York, 1991. 相似文献
5.
Sebastiano A. Delre Wander Jager Marco A. Janssen 《Computational & Mathematical Organization Theory》2007,13(2):185-202
Diffusions of new products and technologies through social networks can be formalized as spreading of infectious diseases.
However, while epidemiological models describe infection in terms of transmissibility, we propose a diffusion model that explicitly
includes consumer decision-making affected by social influences and word-of-mouth processes. In our agent-based model consumers’
probability of adoption depends on the external marketing effort and on the internal influence that each consumer perceives
in his/her personal networks. Maintaining a given marketing effort and assuming its effect on the probability of adoption
as linear, we can study how social processes affect diffusion dynamics and how the speed of the diffusion depends on the network
structure and on consumer heterogeneity. First, we show that the speed of diffusion changes with the degree of randomness
in the network. In markets with high social influence and in which consumers have a sufficiently large local network, the
speed is low in regular networks, it increases in small-world networks and, contrarily to what epidemic models suggest, it
becomes very low again in random networks. Second, we show that heterogeneity helps the diffusion. Ceteris paribus and varying
the degree of heterogeneity in the population of agents simulation results show that the more heterogeneous the population,
the faster the speed of the diffusion. These results can contribute to the development of marketing strategies for the launch
and the dissemination of new products and technologies, especially in turbulent and fashionable markets.
This paper won the best student paper award at the North American Association for Computational Social and Organizational
Science (NAACSOS) Conference 2005, University of Notre Dame, South Bend, Indiana, USA.
Preceding versions of this paper have been presented to the Conference of the North American Association for Computational
Social and Organizational Science (NAACSOS), 2005, University of Notre Dame, South Bend, USA and to the Conference of the
European Social Simulation Association (ESSA), 2005, Koblenz, Germany.
Sebastiano Alessio Delre received his Master Degree in Communication Science at the University of Salerno. After one year collaboration at the Institute
of Science and Technologies of Cognition (ISTC, Rome, Italy), now he is a PhD student at the faculty of economics, University
of Groningen, the Netherlands. His work focus on how different network structures affect market dynamics. His current application
domain concerns Agent-Based Simulation Models for social and economic phenomena like innovation diffusion, fashions and turbulent
market.
Wander Jager is an associate professor of marketing at the University of Groningen. He studied social psychology and obtained his PhD
in the behavioral and social sciences, based on a dissertation about the computer modeling of consumer behaviors in situations
of common resource use. His present research is about consumer decision making, innovation diffusion, market dynamics, crowd
behavior, stock-market dynamics and opinion dynamics. In his work he combines methods of computer simulation and empirical
surveys. He is involved in the management committee of the European Social Simulation Association (ESSA).
Marco Janssen is an assistant professor in the School of Human Evolution and Social Change and in the Department of Computer Science and
Engineering at Arizona State University. He got his degrees in Operations Research and Applied Mathematics. During the last
15 years, he uses computational tools to study social phenomena, especially human-environmental interactions. His present
research focuses on diffusion dynamics, institutional innovation and robustness of social-ecological systems. He combined
computational studies with laboratory and field experiments, case study analysis and archeological data. He is an associate
editor-in-chief of the journal Ecology and Society. 相似文献
6.
We introduce a theory of scan statistics on graphs and apply the ideas to the problem of anomaly detection in a time series
of Enron email graphs.
Previous presentation: Workshop on Link Analysis, Counterterrorism and Security at the SIAM International Conference on Data
Mining, Newport Beach, CA, April 23, 2005.
Carey E. Priebe received the B.S. degree in mathematics from Purdue University in 1984, the M.S. degree in computer science from San Diego
State University in 1988, and the Ph.D. degree in information technology (computational statistics) from George Mason University
in 1993. From 1985 to 1994 he worked as a mathematician and scientist in the US Navy research and development laboratory system.
Since 1994 he has been a professor in the Department of Applied Mathematics and Statistics, Whiting School of Engineering,
Johns Hopkins University, Baltimore, Maryland. At Johns Hopkins, he holds joint appointments in the Department of Computer
Science and the Center for Imaging Science. He is a past President of the Interface Foundation of North America—Computing
Science & Statistics, a past Chair of the Section on Statistical Computing of the American Statistical Association, and on
the editorial boards of Journal of Computational and Graphical Statistics, Computational Statistics and Data Analysis, and
Computational Statistics. His research interests are in computational statistics, kernel and mixture estimates, statistical
pattern recognition, statistical image analysis, and statistical inference for high-dimensional and graph data. He was elected
Fellow of the American Statistical Association in 2002.
John M. Conroy received a B.S. in Mathematics from Saint Joseph's University in 1980 and a Ph.D. in Applied Mathematics from the University
of Maryland in 1986. Since then he has been a research staff member for the IDA Center for Computing Sciences in Bowie, MD.
His research interest is applications of numerical linear algebra. He is a member of the Society for Industrial and Applied
Mathematics, Institute of Electrical and Electronics Engineers (IEEE), and the Association for Computational Linguistics.
David J. Marchette received a B.A. in 1980, and an M.A. in mathematics in 1982, from the University of California at San Diego. He received
a Ph.D. in Computational Sciences and Informatics in 1996 from George Mason University under the direction of Ed Wegman. From
1985–1994 he worked at the Naval Ocean Systems Center in San Diego doing research on pattern recognition and computational
statistics. In 1994 he moved to the Naval Surface Warfare Center in Dahlgren Virginia where he does research in computational
statistics and pattern recognition, primarily applied to image processing, text processing, automatic target recognition and
computer security. Dr. Marchette is a Fellow of the American Statistical Society.
Youngser Park received the B.E. degree in electrical engineering from Inha University in Korea in 1985, the M.S. degree in computer science
from The George Washington University in 1991, and had pursued a doctoral degree there. From 1998 to 2000 he worked at the
Johns Hopkins Medical Institutes as a senior research engineer. Since 2003 he is working as a research analyst in the Center
for Imaging Science at the Johns Hopkins University. His research interests are clustering algorithm, pattern classification,
and data mining. 相似文献
7.
Models of segregation dynamics have examined how individual preferences over neighborhood racial composition determine macroscopic
patterns of segregation. Many fewer models have considered the role of household preferences over other location attributes,
which may compete with preferences over racial composition. We hypothesize that household preferences over location characteristics
other than racial composition affect segregation dynamics in nonlinear ways and that, for a critical range of parameter values,
these competing preferences can qualitatively affect segregation outcomes. To test this hypothesis, we develop a dynamic agent-based
model that examines macro-level patterns of segregation as the result of interdependent household location choices. The model
incorporates household preferences over multiple neighborhood features, some of which are endogenous to residential location
patterns, and allows for income heterogeneity across races and among households of the same race. Preliminary findings indicate
that patterns of segregation can emerge even when individuals are wholly indifferent to neighborhood racial composition, due
to competing preferences over neighborhood density. Further, the model shows a strong tendency to concentrate affluent families
in a small number of suburbs, potentially mimicking recent empirical findings on favored quarters in metropolitan areas.
This paper was the first runner-up for the 2004 NAACSOS best paper award.
Kan Chen is an associate professor in the Department of Computational Science at the National University of Singapore. His recent
research interests include spatial and temporal scaling in driven, dissipative systems, applications of self-organized criticality,
dynamics of earthquakes, and computational finance. He received a B.Sc. in physics from the University of Science and Technology
of China (1983) and a Ph.D. in physics from Ohio State University (1988).
Elena Irwin is an associate professor in the Department of Agricultural, Environmental, and Development Economics at Ohio State University.
Her research interests include land use change, urban sprawl, household location decisions, and the value of open space. This
research applies theory and modeling techniques from the fields of spatial and regional economics, including the application
of spatial econometrics and geographic information systems (GIS). She received a B.A. in German and History from Washington
University in St. Louis (1988) and a Ph.D. in Agricultural and Resource Economics from the University of Maryland (1998).
Ciriyam Jayaprakash is a Professor in the Department of Physics at the Ohio State University. His recent research interests include spatially
extended nonlinear systems including fully-developed turbulence, genetic regulatory networks, and applications of statistical
mechanical techniques to financial and social sciences. He received an M.S. in Physics from the Indian Institute of Technology,
Kanpur (1973), an M.S. in Physics from Caltech (1975) and a Ph.D in Physics from the University of Illinois at Urbana-Champaign
(1979).
Keith Warren is an assistant professor in the College of Social Work at Ohio State University. His research interests focus on interpersonal
interactions in the development and solution of social problems, particularly those of urban areas such as segregation, substance
abuse and increased interpersonal violence. He received a B.A in Behavioral Science from Warren Wilson College (1984), and
a Ph.D. in Social Work from the University of Texas at Austin (1998) 相似文献
8.
A normative framework for agent-based systems 总被引:1,自引:0,他引:1
Fabiola López y López Michael Luck Mark d’Inverno 《Computational & Mathematical Organization Theory》2006,12(2-3):227-250
One of the key issues in the computational representation of open societies relates to the introduction of norms that help to cope with the heterogeneity, the autonomy and the diversity of interests among their members. Research regarding
this issue presents two omissions. One is the lack of a canonical model of norms that facilitates their implementation, and
that allows us to describe the processes of reasoning about norms. The other refers to considering, in the model of normative
multi-agent systems, the perspective of individual agents and what they might need to effectively reason about the society
in which they participate. Both are the concerns of this paper, and the main objective is to present a formal normative framework
for agent-based systems that facilitates their implementation.
F. López y López is researcher of the Computer Science Faculty at the Benemérita Universidad Autónoma de Puebla in México, from where she
got her first degree. She also gained a MSc in Computation from the Universidad Nacional Autónoma de México and a PhD in Computer
Science from the University of Southampton in the United Kingdom. She is leading several theoretical and practical projects
that use multi-agent systems as the main paradigm. Her research has been focused on Autonomous Normative Agents and Normative
Multi-Agent Systems and she has published over 20 articles in these and related topics.
M. Luck is Professor of Computer Science in the Intelligence, Agents, Multimedia Group of the School of Electronics and Computer
Science at the University of Southampton, where he carries out research into the theory and practice of agent technology.
He has published over 150 articles in these and related areas, both alone and in collaboration with others, and has published
eight books. He is a member of the Executive Committee of AgentLink III, the European Network of Excellence for Agent-Based
Computing. He is a co-founder of the European Multi-Agent Systems workshop series, is co-founder and Chair of the steering
committee of the UK Multi-Agent Systems Workshops (UKMAS), and was a member of the Management Board of Agentcities.NET. Professor
Luck is also a steering committee member for the Central and Eastern European Conference on Multi-Agent Systems. He is series
editor for Artech House’s Agent Oriented Systems series, and an editorial board member of the Journal of Autonomous Agents
and Multi-Agent Systems, the International Journal of Agent-Oriented Software Engineering, and ACM Transactions on Autonomous
and Adaptive Systems.
M. d’Inverno gained a BA in Mathematics and an MSc in Computation both from Oxford University. He also was awarded a PhD from University
College London. He joined the University of Westminster in 1992 as a Lecturer, became a senior lecturer in 1998, a reader
in 1999 and was appointed professor of computer science in 2001. He is interested in formal, principled approaches to modelling
both natural and artificial systems in a computational setting. The main strand to this research, focuses on the application
of formal methods in providing models of intelligent agent and multi-agent systems. His approach has sought to take a structured
approach to the development of practical agent systems from theoretical models. He has published over 70 articles in these
areas and has published four books and edited collections. 相似文献
9.
Marco Alberti Marco Gavanelli Evelina Lamma Paola Mello Paolo Torroni Giovanni Sartor 《Computational & Mathematical Organization Theory》2006,12(2-3):205-225
Deontic concepts and operators have been widely used in several fields where representation of norms is needed, including
legal reasoning and normative multi-agent systems.
The EU-funded SOCS project has provided a language to specify the agent interaction in open multi-agent systems. The language
is equipped with a declarative semantics based on abductive logic programming, and an operational semantics consisting of
a (sound and complete) abductive proof procedure. In the SOCS framework, the specification is used directly as a program for
the verification procedure.
In this paper, we propose a mapping of the usual deontic operators (obligations, prohibition, permission) to language entities,
called expectations, available in the SOCS social framework. Although expectations and deontic operators can be quite different
from a philosophical viewpoint, we support our mapping by showing a similarity between the abductive semantics for expectations
and the Kripke semantics that can be given to deontic operators.
The main purpose of this work is to make the computational machinery from the SOCS social framework available for the specification
and verification of systems by means of deontic operators.
Marco Alberti received his laurea degree in Electronic Engineering in 2001 and his Ph.D. in Information Engineering in 2005 from the University
of Ferrara, Italy. His research interests include constraint logic programming and abductive logic programming, applied in
particular to the specification and verification of multi-agent systems. He has been involved as a research assistants in
national and European research projects. He currently has a post-doc position in the Department of Engineering at the University
of Ferrara.
Marco Gavanelli is currently assistant professor in the Department of Engineering at the University of Ferrara, Italy. He graduated in Computer
Science Engineering in 1998 at the University of Bologna, Italy. He got his Ph.D. in 2002 at Ferrara University. His research
interest include Artificial Intelligence, Constraint Logic Programming, Multi-criteria Optimisation, Abductive Logic Programming,
Multi-Agent Systems. He is a member of ALP (the Association for Logic Programming) and AI*IA (the Italian Association for
Artificial Intelligence). He has organised workshops, and is author of more than 30 publications between journals and conference
proceedings.
Evelina Lamma received her degree in Electronic Engineering from University of Bologna, Italy, in 1985 and her Ph.D. degree in Computer
Science in 1990. Currently she is Full Professor at the Faculty of Engineering of the University of Ferrara where she teaches
Artificial Intelligence and Foundations of Computer Science. Her research activity focuses around:
– programming languages (logic languages, modular and object-oriented programming);
– artificial intelligence;
– knowledge representation;
– intelligent agents and multi-agent systems;
– machine learning.
Her research has covered implementation, application and theoretical aspects. She took part to several national and international
research projects. She was responsible of the research group at the Dipartimento di Ingegneria of the University of Ferrara
in the UE ITS-2001-32530 Project (named SOCS), in the the context of the UE V Framework Programme - Global Computing Action.
Paola Mello received her degree in Electronic Engineering from the University of Bologna, Italy, in 1982, and her Ph.D. degree in Computer
Science in 1989. Since 1994 she has been Full Professor. She is enrolled, at present, at the Faculty of Engineering of the
University of Bologna (Italy), where she teaches Artificial Intelligence. Her research activity focuses on programming languages,
with particular reference to logic languages and their extensions, artificial intelligence, knowledge representation, expert
systems with particular emphasis on medical applications, and multi-agent systems. Her research has covered implementation,
application and theoretical aspects and is presented in several national and international publications. She took part to
several national and international research projects in the context of computational logic.
Giovanni Sartor is Marie-Curie professor of Legal informatics and Legal Theory at the European University Institute of Florence and professor
of Computer and Law at the University of Bologna (on leave), after obtaining a PhD at the European University Institute (Florence),
working at the Court of Justice of the European Union (Luxembourg), being a researcher at the Italian National Council of
Research (ITTIG, Florence), and holding the chair in Jurisprudence at Queen’s University of Belfast (where he now is honorary
professor). He is co-editor of the Artificial Intelligence and Law Journal and has published widely in legal philosophy, computational
logic, legislation technique, and computer law.
Paolo Torroni is Assistant Professor in computing at the Faculty of Engineering of the University of Bologna, Italy. He obtained a PhD
in Computer Science and Electronic Engineering in 2002, with a dissertation on logic-based agent reasoning and interaction.
His research interests mainly focus on computational logic and multi-agent systems research, including logic programming,
abductive and hypothetical reasoning, agent interaction, dialogue, negotiation, and argumentation. He is in the steering committee
of the CLIMA and DALT international workshops and of the Italian logic programming interest group GULP. 相似文献
10.
The models used in social simulation to date have mostly been very simplistic cognitively, with little attention paid to the
details of individual cognition. This work proposes a more cognitively realistic approach to social simulation. It begins
with a model created by Gilbert (1997) for capturing the growth of academic science. Gilbert’s model, which was equation-based,
is replaced here by an agent-based model, with the cognitive architecture CLARION providing greater cognitive realism. Using
this cognitive agent model, results comparable to previous simulations and to human data are obtained. It is found that while
different cognitive settings may affect the aggregate number of scientific articles produced, they do not generally lead to
different distributions of number of articles per author. The paper concludes with a discussion of the correspondence between the model and the constructivist
view of academic science. It is argued that using more cognitively realistic models in simulations may lead to novel insights.
Isaac Naveh obtained a master’s degree in computer science at the University of Missouri. His research interests include hybrid cognitive
models and multi-agent learning.
Ron Sun is Professor of Cognitive Science at Rensselaer Polytechnic Institute, and formerly the James C. Dowell Professor of Engineering
and Professor of Computer Science at University of Missouri-Columbia. He received his Ph.D in 1992 from Brandeis University.
His research interest centers around studies of cognition, especially in the areas of cognitive architectures, human reasoning
and learning, cognitive social simulation, and hybrid connectionist models. For his paper on integrating rule-based and connectionist
models for accounting for human everyday reasoning, he received the 1991 David Marr Award from Cognitive Science Society.
He is the founding co-editor-in-chief of the journal Cognitive Systems Research, and also serves on the editorial boards of
many other journals. He is the general chair and program chair for CogSci 2006, and a member of the Governing Board of International
Neural Networks Society. His URL is: http://www.cogsci.rpi.edu/~rsun 相似文献
11.
Hans O. Andersen 《School science and mathematics》2000,100(6):298-303
Dr. Andersen has worked as a science education professor at Indiana University, Bloomington, since 1966. He has authored six textbooks and over 100 articles on science teacher preparation, science teaching, and science curriculum. He has served as president of the Association for the Education of Teachers in Science, as chair of the Education Section of the American Association for the Advancement of Science, and as a president of the National Science Teachers Association. Among many other honors, he has received the Distinguished Teaching Award at Indiana University and Robert E. Carlton Award for Distinguished National Leadership in Science Education (NSTA). 相似文献
12.
Introduction to normative multiagent systems 总被引:1,自引:0,他引:1
Guido Boella Leendert van der Torre Harko Verhagen 《Computational & Mathematical Organization Theory》2006,12(2-3):71-79
This article introduces the research issues related to and definition of normative multiagent systems. It also describes the
papers selected from NorMAS05 that are part of this double special issue and relates the papers to each other.
Guido Boella received the PhD degree at the University of Torino in 2000.He is currently professor at the Department of Computer Science
of the University of Torino. His research interests include multi-agent systems, in particular, normative systems, institutions
and roles using qualitative decision theory.He is the co-chair of the firstworkshops on normative multi-agent systems (NorMas05),
on coordination and organization (CoOrg05), and the AAAI Fall Symposium on roles (Roles05).
Leendert van der Torre received the Ph.D. degree in computer science fromErasmus University Rotterdam, The Netherlands, in 1997. He is currently
a Full Professor at the University of Luxembourg. He has developed the so-called input/output logics and the BOID agent architecture.
His current research interests include deontic logic, qualitative game theory, and security and coordination in normative
multiagent systems.
Harko Verhagen received his Ph.D. degree in computer and systems sciences from Stockholm University (Sweden) in 2000 and is currently an
associate professor at the department. His research has focussed on simulation of organizational behaviour, simulation as
a scientific method, the use of sociological theories in multiagent systems research and more in particular theories on norms
and autonomy. 相似文献
13.
Using an Iterated Prisoner's Dilemma with Exit Option to Study Alliance Behavior: Results of a Tournament and Simulation 总被引:1,自引:0,他引:1
Nearly half of all strategic alliances fail (Park and Russo, 1996; Dyer et al., 2001), often because of opportunistic behavior
by one party or the other. We use a tournament and simulation to study strategies in an iterated prisoner's dilemma game with
exit option to shed light on how a firm should react to an opportunistic partner. Our results indicate that a firm should
give an alliance partner a second chance following an opportunistic act but that subsequent behavior should be contingent
on the value of the next best opportunity outside the alliance. Firms should be more forgiving if the potential benefits from
the alliance exceed other opportunities. The strategies were also found to be robust across a wide range of game lengths.
The implications of these results for alliance strategies are discussed.
Steven E. Phelan received his PhD in economics from La Trobe University (Australia) in 1998. Following five years at the University of Texas
at Dallas, he joined the faculty of the University of Nevada Las Vegas in 2003. Dr. Phelan's research interests include competitive
dynamics, organizational efficiency, acquisition and alliance performance, and entrepreneurial competence. His methods of
choice to study these phenomena include agent-based modelling, experimental game theory, and event studies. Prior to joining
academia, Dr. Phelan held executive positions in the telecommunications and airline industries and was a principal partner
in Bridges Management Group, a consultancy specializing in strategic investment decisions.
Richard J. Arend is a graduate of the University of British Columbia's doctoral program in Policy Analysis and Strategy. He is on the Management
faculty of the University of Nevada, Las Vegas, arriving most recently from the Management faculty of New York University's
Stern School of Business. Dr. Arend's interests lie in the analysis of unusual modes of firm value creation and destruction,
where he has published in several top journals. He is a professional engineer with work and consulting experience in aerospace
and computing.
Darryl A. Seale joined the faculty of UNLV in 1999, following three years at Kent State University and the University of Alabama in Huntsville.
Prior to Alabama, he completed his Ph.D. and M.S. degrees in Business Administration at the University of Arizona, his M.B.A.
from Penn State University, and spent over ten years in management and market planning positions in the health care industry.
Professor Seale's research interests include strategic decision making, bargaining and negotiation, and behavioral game theory.
His research has been funded by the National Science Foundation and has been published in top-tier journals including Management
Science, OBHDP, Games and Economic Behavior, and Strategic Management Journal. His teaching interests include business policy/strategy,
managerial decision making, and bargaining and negotiation. 相似文献
14.
Lawrence A. Kuznar William Frederick 《Computational & Mathematical Organization Theory》2007,13(1):29-37
Nepotism has been the primary influence on political behavior throughout human history. Despite the spread of democracy in the 20th century, nepotistic regimes have hardly disappeared. Nepotism heavily influences political activity throughout the developing world, Middle East, and central Asia where family ties are essential for gaining access to power, state resources, and privileges. Rebelling against such nepotistic regimes is difficult and risky. RiskTaker is an agent-based model we developed for testing the influences of various social forces on risk taking behavior, including the formulation of rebellious coalitions. We use RiskTaker to examine the influence of nepotism on the distribution of wealth and social status. Nepotism heavily skews the distribution of wealth and status, leading to the formation of opposing coalitions and exacerbating social unrest.This paper was tied for Best Paper, NAACSOS (North American Association for Computational Social and Organizational Science) Annual Conference 2005, June 26–28, Notre Dame. Robert Sedlmeyer, Department of Computer Science, Indiana University – Purdue University, Fort Wayne provided programming for the RiskTaker model.
Lawrence A. Kuznar is a professor of anthropology and director of the Decision Sciences and Theory Institute at Indiana University—Purdue University, Fort Wayne. He has conducted fieldwork among Aymara Indians in Andean Peru and the Navajo of the American southwest. His research interests include computer modeling, theories of risk taking and conflict, terrorism, social evolution, and scientific epistemology. He has authored articles in Ecological Economics (with W. Frederick), Current Anthropology, American Anthropologist, Mathematical Anthropology and Culture Theory and Journal of Anthropological Research, and published two books (Awatimarka Harcourt Brace, 1995 and Reclaiming a Scientific Anthropology Altamira Press, 1997) and two edited volumes.
William Frederick has served as a faculty member in the departments of mathematical
sciences and the department of computer sciences at Indiana University—Purdue University, Fort Wayne since 1979. His primary interests include mathematical modeling, game theory, and genetic algorithms. 相似文献
15.
Mathematical models are presented for studying the value of leadership in a team where the members interact with each other. The models are based on a leader’s role of motivating each team member to perform closer to his/her maximum ability. These models include controllable parameters whose values reflect the amount of task interdependence among the workers as well as the motivational skill and variability in the skill of the leader. Confirming results—such as the fact that the skill level of the leader is a critical factor in the expected performance of the team—establish credibility in the models. Mathematical analysis and computer simulations are used to provide new managerial insights into the value of the leader—such as the fact that the skill of the leader can be more important than controlling the amount of interdependence among the team members and that having a choice of multiple leaders with no particular motivating skill is beneficial to the performance of small teams but not to large teams.Daniel Solow received a B.S. in Mathematics from Carnegie-Mellon, an M.S. in Operations Research from the University of California at Berkeley, and a Ph. D. in Operations Research from Stanford University. He has been a professor at Case Western Reserve University since 1978. His research interests include complex systems, discrete, linear, and nonlinear optimization. He has also developed systematic methods for teaching mathematical proofs, computer programming, and operations research.Sandy Kristin Piderit is an assistant professor of organizational behavior at the Weatherhead School of Management at Case Western Reserve University, and earned her Ph.D. from the University of Michigan. She studies the roles of relationships among coworkers on their performance and satisfaction with their work environments, and has published studies in the Academy of Management Review, the Journal of Management Studies, and Management Science.Apostolos Burnetas received a Diploma in Electrical Engineering from National Technical University in Athens, Greece, and an M.B.A. and Ph.D. in Operations Research from Rutgers University. He has been at the Department of Operations at Case Western Reserve University and is currently an Associate Professor at the Department of Mathematics at the University of Athens. His research interests include stochastic models and optimization, complex systems, and applications in queueing systems, supply chain and the interface of operations with finance.Chartchai Leenawong received a B.S. in Mathematics from Chulalongkorn University in Bangkok, an M.S. in Computer Science from the Asian Institute of Technology in Bangkok, and a Ph.D. in Operations Research from Case Western Reserve University. His research interests include mathematical modeling of complex systems as applied to business organizations. He has been a professor at King Mongkut’s Institute of Technology Ladkrabang, Bangkok, Thailand since 2002. 相似文献
16.
The Enron email corpus is appealing to researchers because it represents a rich temporal record of internal communication
within a large, real-world organization facing a severe and survival-threatening crisis. We describe how we enhanced the original
corpus database and present findings from our investigation undertaken with a social network analytic perspective. We explore
the dynamics of the structure and properties of the organizational communication network, as well as the characteristics and
patterns of communicative behavior of the employees from different organizational levels. We found that during the crisis
period, communication among employees became more diverse with respect to established contacts and formal roles. Also during
the crisis period, previously disconnected employees began to engage in mutual communication, so that interpersonal communication
was intensified and spread through the network, bypassing formal chains of communication. The findings of this study provide
valuable insight into a real-world organizational crisis, which may be further used for validating or developing theories
and dynamic models of organizational crises; thereby leading to a better understanding of the underlying causes of, and response
to, organization failure.
Jana Diesner is a Research Associate and Linguistic Programmer at the Center for Computational Analysis of Social and Organizational Systems
at the School of Computer Science (CASOS), Carnegie Mellon University (CMU). She received her Masters in Communications from
Dresden University of Technology in 2003. She had been a research scholar at the Institute for Complex Engineered System at
CMU in 2001 and 2002. Her research combines computational linguistics, social network analysis and computational organization
theory.
Terrill L. Frantz is a post-doc researcher at the Center for Computational Analysis of Social and Organizational Systems (CASOS) in the School
of Computer Science at Carnegie Mellon University. His research involves studying the dynamics of organization social-networks
and behavior via computer modeling and simulation. He is developing an expertise in workforce integration strategy and policy
evaluation during organization mergers. He earned his doctorate (Ed.D. in Organization Change) from Pepperdine University,
a MBA from New York University and a BS in Business Administration (Computer Systems Management) from Drexel University. Prior
to entering academic research, for nearly 20 years he was a software applications development manager in the global financial
services and industrial chemicals industries; most recently as a Vice President in Information Technology at Morgan Stanley
in Hong Kong, New York and London.
Kathleen M. Carley is a professor at the Institute for Software Research International in the School of Computer Science at Carnegie Mellon
University. She is the director of the center for Computational Analysis of Social and Organizational Systems (CASOS) <http://www.casos.cs.cmu.edu/>,
a university wide interdisciplinary center that brings together network analysis, computer science and organization science
(www.casos.ece.cmu.edu) and has an associated NSF funded training program for Ph.D. students. She carries out research that
combines cognitive science, social networks and computer science to address complex social and organizational problems. Her
specific research areas are computational social and organization theory, group, organizational and social adaptation and
evolution, social and dynamic network analysis, computational text analysis, and the impact of telecommunication technologies
and policy on communication, information diffusion, disease contagion and response within and among groups particularly in
disaster or crisis situations. 相似文献
17.
《Optimization》2012,61(4):549-570
The best spectral conjugate gradient algorithm by (Birgin, E. and Martínez, J.M., 2001, A spectral conjugate gradient method for unconstrained optimization. Applied Mathematics and Optimization, 43, 117–128). which is mainly a scaled variant of (Perry, J.M., 1977, A class of Conjugate gradient algorithms with a two step varaiable metric memory, Discussion Paper 269, Center for Mathematical Studies in Economics and Management Science, Northwestern University), is modified in such a way as to overcome the lack of positive definiteness of the matrix defining the search direction. This modification is based on the quasi-Newton BFGS updating formula. The computational scheme is embedded into the restart philosophy of Beale–Powell. The parameter scaling the gradient is selected as spectral gradient or in an anticipative way by means of a formula using the function values in two successive points. In very mild conditions it is shown that, for strongly convex functions, the algorithm is global convergent. Computational results and performance profiles for a set consisting of 700 unconstrained optimization problems show that this new scaled nonlinear conjugate gradient algorithm substantially outperforms known conjugate gradient methods including: the spectral conjugate gradient SCG by Birgin and Martínez, the scaled Fletcher and Reeves, the Polak and Ribière algorithms and the CONMIN by (Shanno, D.F. and Phua, K.H., 1976, Algorithm 500, Minimization of unconstrained multivariate functions. ACM Transactions on Mathematical Software, 2, 87–94). 相似文献
18.
《Optimization》2012,61(3-4):393-395
Grubbstrom, R. W.; H. H. Hinterhuber (eds), J. Lundquist (Associate editor): Production Economics: Issues and Challenges for the 90's. Proceedings of the Sixth International Working Seminar on Production Economics, Igls, Austria, February 19-23, 1990. Elsevier Science Publishers B. V., Amsterdam, London, New York, Tokyo, 1991, 480 pp., ISBN 0-444-89422-5. 相似文献
19.
Graph Theoretic and Spectral Analysis of Enron Email Data 总被引:1,自引:0,他引:1
Analysis of social networks to identify communities and model their evolution has been an active area of recent research.
This paper analyzes the Enron email data set to discover structures within the organization. The analysis is based on constructing
an email graph and studying its properties with both graph theoretical and spectral analysis techniques. The graph theoretical
analysis includes the computation of several graph metrics such as degree distribution, average distance ratio, clustering
coefficient and compactness over the email graph. The spectral analysis shows that the email adjacency matrix has a rank-2
approximation. It is shown that preprocessing of data has significant impact on the results, thus a standard form is needed
for establishing a benchmark data.
Anurat Chapanond is currently a Ph.D. student in Computer Science, RPI. Anurat graduated B. Eng. degree in Computer Engineering from Chiangmai
University (Thailand) in 1997, M. S. in Computer Science from Columbia University in 2002. His research interest is in web
data mining analyses and algorithms.
M.S. Krishnamoorthy received the B.E. degree (with honors) from Madras University in 1969, the M. Tech degree in Electrical Engineering from
the Indian Institute of Technology, Kanpur, in 1971, and the Ph. D. degree in Computer Science, also from the Indian Institute
of Technology, in 1976.
From 1976 to 1979, he was an Assistant Professor of Computer Science at the Indian Institute of Technology, Kanpur. From 1979
to 1985, he was an Assistant Professor of Computer Science at Rensselaer Polytechnic Institute, Troy, NY, and since, 1985,
he has been an Associate Professor of Computer Science at Rensselaer. Dr. Krishnamoorthy's research interests are in the design
and analysis of combinatorial and algebraic algorithms, visualization algorithms and programming environments.
Bulent Yener is an Associate Professor in the Department of Computer Science and Co-Director of Pervasive Computing and Networking Center
at Rensselaer Polytechnic Institute in Troy, New York. He is also a member of Griffiss Institute of Information Assurance.
Dr. Yener received MS. and Ph.D. degrees in Computer Science, both from Columbia University, in 1987 and 1994, respectively.
Before joining to RPI, he was a Member of Technical Staff at the Bell Laboratories in Murray Hill, New Jersey.
His current research interests include bioinformatics, medical informtatics, routing problems in wireless networks, security
and information assurance, intelligence and security informatics. He has served on the Technical Program Committee of leading
IEEE conferences and workshops. Currently He is an associate editor of ACM/Kluwer Winet journal and the IEEE Network Magazine.
Dr. Yener is a Senior Member of the IEEE Computer Society. 相似文献
20.
In research and application, social networks are increasingly extracted from relationships inferred by name collocations in
text-based documents. Despite the fact that names represent real entities, names are not unique identifiers and it is often
unclear when two name observations correspond to the same underlying entity. One confounder stems from ambiguity, in which
the same name correctly references multiple entities. Prior name disambiguation methods measured similarity between two names
as a function of their respective documents. In this paper, we propose an alternative similarity metric based on the probability
of walking from one ambiguous name to another in a random walk of the social network constructed from all documents. We experimentally
validate our model on actor-actor relationships derived from the Internet Movie Database. Using a global similarity threshold,
we demonstrate random walks achieve a significant increase in disambiguation capability in comparison to prior models.
Bradley A. Malin is a Ph.D. candidate in the School of Computer Science at Carnegie Mellon University. He is an NSF IGERT fellow in the Center
for Computational Analysis of Social and Organizational Systems (CASOS) and a researcher at the Laboratory for International
Data Privacy. His research is interdisciplinary and combines aspects of bioinformatics, data forensics, data privacy and security,
entity resolution, and public policy. He has developed learning algorithms for surveillance in distributed systems and designed
formal models for the evaluation and the improvement of privacy enhancing technologies in real world environments, including
healthcare and the Internet. His research on privacy in genomic databases has received several awards from the American Medical
Informatics Association and has been cited in congressional briefings on health data privacy. He currently serves as managing
editor of the Journal of Privacy Technology.
Edoardo M. Airoldi is a Ph.D. student in the School of Computer Science at Carnegie Mellon University. Currently, he is a researcher in the
CASOS group and at the Center for Automated Learning and Discovery. His methodology is based on probability theory, approximation
theorems, discrete mathematics and their geometries. His research interests include data mining and machine learning techniques
for temporal and relational data, data linkage and data privacy, with important applications to dynamic networks, biological
sequences and large collections of texts. His research on dynamic network tomography is the state-of-the-art for recovering
information about who is communicating to whom in a network, and was awarded honors from the ACM SIG-KDD community. Several
companies focusing on information extraction have adopted his methodology for text analysis. He is currently investigating
practical and theoretical aspects of hierarchical mixture models for temporal and relational data, and an abstract theory
of data linkage.
Kathleen M. Carley is a Professor of Computer Science in ISRI, School of Computer Science at Carnegie Mellon University. She received her Ph.D.
from Harvard in Sociology. Her research combines cognitive science, social and dynamic networks, and computer science (particularly
artificial intelligence and machine learning techniques) to address complex social and organizational problems. Her specific
research areas are computational social and organization science, social adaptation and evolution, social and dynamic network
analysis, and computational text analysis. Her models meld multi-agent technology with network dynamics and empirical data.
Three of the large-scale tools she and the CASOS group have developed are: BioWar a city, scale model of weaponized biological
attacks and response; Construct a models of the co-evolution of social and knowledge networks; and ORA a statistical toolkit
for dynamic social Network data. 相似文献