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
Reputation
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.
Abstract
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.