Normative Multi-Agent Systems by Giulia Andrighetto and Guido Governatori and Pablo Noriega and Leendert W. N. van der Torre
As research in Multi-Agent Systems (MAS) has been expanding its focus from from the individual, cognitive focussed, agent models to models of socially situated agents, MAS researchers have been showing rising interest in social theories. Particular attention has been given to normative concepts because it is expected that norms could play as key a role in articulating agent interactions as the one norms play in human social intelligence. Thus, the label of “normative multi-agent system” has been attached to systems where individual and collective behaviour is affected by norms. This book is not a state of the art of normative multi-agent systems, nor a systematic description of the key concepts, or a compendium of the most salient challenges. However, the reader will find in its chapters something of each of these three contents because Normative Multi-Agent Systems is an effort to clarify the ideas behind the label and to put in perspective the work that is being done in this area.
(Social) Norm Dynamics, Giulia Andrighetto, Cristiano Castelfranchi, Eunate Mayor, John McBreen, Maite Lopez-Sanchez, and Simon Parsons
Simulation and NorMAS, Tina Balke, Stephen Cranefield, Gennaro Di Tosto, Samhar Mahmoud, Mario Paolucci, Bastin Tony Roy Savarimuthu, and Harko Verhagen
We are proud to announce:
the paper on peer review published on ACS:
FRANCISCO GRIMALDO and MARIO PAOLUCCI, Advs. Complex Syst. DOI: 10.1142/S0219525913500045
A SIMULATION OF DISAGREEMENT FOR CONTROL OF RATIONAL CHEATING IN PEER REVIEW
Understanding the peer review process could help research and shed light on the mechanisms that underlie crowdsourcing. In this paper, we present an agent-based model of peer review built on three entities — the paper, the scientist and the conference. The system is implemented on a BDI platform (Jason) that allows to define a rich model of scoring, evaluating and selecting papers for conferences. Then, we propose a programme committee update mechanism based on disagreement control that is able to remove reviewers applying a strategy aimed to prevent papers better than their own to be accepted (“rational cheating”). We analyze a homogeneous scenario, where all conferences aim to the same level of quality, and a heterogeneous scenario, in which conferences request different qualities, showing how this affects the update mechanism proposed. We also present a first step toward an empirical validation of our model that compares the amount of disagreements found in real conferences with that obtained in our simulations.
Keywords: Artificial social systems; peer review; agent-based simulation; trust reliability and reputation
and the chapter on Reputation in the book “Simulating Social Complexity”:
Francesca Giardini, Rosaria Conte, Mario Paolucci
Why Read This Chapter?
To understand the different conceptions underlying reputation in simulations up to the current time and to get to know some of the approaches to implementing reputation mechanisms, which are more cognitively sophisticated.
In this chapter, the role of reputation as a distributed instrument for social order is addressed. A short review of the state of the art will show the role of reputation in promoting (a) social control in cooperative contexts – like social groups and subgroups – and (b) partner selection in competitive contexts, like (e-) markets and industrial districts. In the initial section, current mechanisms of reputation – be they applied to electronic markets or MAS – will be shown to have poor theoretical backgrounds, missing almost completely the cognitive and social properties of the phenomenon under study. In the rest of the chapter a social cognitive model of reputation developed in the last decade by some of the authors will be presented. Its simulation-based applications to the theoretical study of norm-abiding behaviour, partner selection and to the refinement and improvement of current reputation mechanisms will be discussed. Final remarks and ideas for future research will conclude the chapter.
The 1st Workshop on Parallel and Distributed Agent-Based Simulations is a satellite Workshop of Euro-Par 2013 (Aachen, Germany, Aug. 26th – Aug. 30th, 2013).
Agent-Based Simulation Models are an increasingly popular tool for research and management in many fields such as ecology, economics, sociology, etc..
In some fields, such as social sciences, these models are seen as a key instrument to the generative approach, essential for understanding complex social phenomena. But also in policy-making, biology, military simulations, control of mobile robots and economics, the relevance and effectiveness of Agent-Based Simulation Models is recently recognized.
Computer science community has responded to the need for platforms that can help the development and testing of new models in each specific field by providing tools, libraries and frameworks that speed up and make massive simulations.
The key objective of this workshop is to bring together the researchers that are interested in getting more performances from their simulations, by using:
- synchronized, many-core simulations (e.g., GPUs),
- strongly coupled, parallel simulations (e.g. MPI)
- loosely coupled, distributed simulations (distributed heterogeneous setting).
The workshop will be held on August 26th 2013.
Distributed Punishment as a Norm-Signalling Tool@AAMAS2012
As the FuturICT coordination action rushes ahead, we point out some of the dissemination materials that this lab helped to build:
Videos with the FututICT message: a documentary on FuturICT and Rosaria’s interview
Leaflets on the Living Earth Simulator and on the Crime Exploratory.
Two Scenarios for Crowdsourcing Simulation
In this paper, we trace a line through the recent story of agent-based social simulation from the point of view of the LABBS, the laboratory of agent-based social simulation that Cristiano Castelfranchi has contributed to create and helped grow. From this observatory, we deploy a set of arguments defending the need for social simulation as one of the best chances we have to make a much needed step forward in the scientific endeavor of the twenty first century: understanding society. Building on these arguments, we point out several reasons that caused social simulation to fall several measures short of the big challenge, discussing some famous examples from the literature. We then introduce the concept of crowdsourcing, trying to elaborate on how it could reshape this methodology for computational social science.
R. Conte, M. Paolucci
Keywords: Agent Based Modeling, Social Simulation, Computational Social Science, Generative Explanation, micro-macro
Link to the preprint
There will be a special session on the Social Complexity of Informal Value Exchange at the 7th European Social Simulation Association Conference, September 19-23, 2011, Montpellier – France, chaired by Bruce Edmonds.
Last year’s SCIVE
The Summer school will take place in Trento, 27 June – 8 July 2011
Intensive course in Evolution of Social Preferences
Guest lecturers include: Werner Gueth, Max Planck Institute, Jena – Honorary lecturer, Sam Bowles, Santa Fe Institute and University of Siena, Simon Gaechter, University of Nottingham, Ugo Pagano, University of Siena, J. Peter Richerson, University of California Davis, Luigi Bonatti, University of Trento, Rosaria Conte, ISTC-CNR, Rome.