Mario Paolucci

On representation and aggregation of social evaluations in computational trust and reputation models

Interest for computational trust and reputation models is on the rise. One of the most important aspects of these models is how they deal with information received from other individuals. More generally, the critical choice is how to represent and how to aggregate social evaluations. In this article, we make an analysis of the current approaches of representation and aggregation of social evaluations under the guidelines of a set of basic requirements. Then we present two different proposals of dealing with uncertainty in the context of the Repage system [J. Sabater, M. Paolucci, R. Conte, Repage: Reputation and image among limited autonomous partners, Journal of Artificial Societies and Social Simulation 9 (2). URL http://jasss.soc.surrey.ac.uk/9/2/3.html], a computational module for management of reputational information based on a cognitive model of imAGE, REPutation and their interplay already developed by the authors. We finally discuss these two proposals in the context of several examples.

On agent-based modeling and computational social science.

In the first part of the paper, the field of agent-based modeling (ABM) is discussed focusing on the role of generative theories, aiming at explaining phenomena by growing them. After a brief analysis of the major strengths of the field some crucial weaknesses are analyzed. In particular, the generative power of ABM is found to have been underexploited, as the pressure for simple recipes has prevailed and shadowed the application of rich cognitive models. In the second part of the paper, the renewal of interest for Computational Social Science (CSS) is focused upon, and several of its variants, such as deductive, generative, and complex CSS, are identified and described. In the concluding remarks, an interdisciplinary variant, which takes after ABM, reconciling it with the quantitative one, is proposed as a fundamental requirement for a new program of the CSS.

Reputation-based decisions for logic-based cognitive agents

Computational trust and reputation models have been recognized as one of the key technologies required to design and implement agent systems. These models manage and aggregate the information needed by agents to efficiently perform partner selection in uncertain situations. For simple applications, a game theoretical approach similar to that used in most models can suffice. However, if we want to undertake problems found in socially complex virtual societies, we need more sophisticated trust and reputation systems. In this context, reputation-based decisions that agents make take on special relevance and can be as important as the reputation model itself. In this paper, we propose a possible integration of a cognitive reputation model, Repage, into a cognitive BDI agent. First, we specify a belief logic capable to capture the semantics of Repage information, which encodes probabilities. This logic is defined by means of a two first-order languages hierarchy, allowing the specification of axioms as first-order theories. The belief logic integrates the information coming from Repage in terms if image and reputation, and combines them, defining a typology of agents depending of such combination. We use this logic to build a complete graded BDI model specified as a multi-context system where beliefs, desires, intentions and plans interact among each other to perform a BDI reasoning. We conclude the paper with an example and a related work section that compares our approach with current state-of-the-art models.

Multi-Agent-Based Simulation VIII

MABS Celebrates Its 10th Anniversary!.- MABS Celebrates Its 10th Anniversary!.- Architectures.- System Issues in Multi-agent Simulation of Large Crowds.- Middleware Support for Performance Improvement of MABS Applications in the Grid Environment.- E Pluribus Unum: Polyagent and Delegate MAS Architectures.- A Multi-agent Model for the Micro-to-Macro Linking Derived from a Computational View of the Social Systems Theory by Luhmann.- Teams, Learning, Education.- Agent-Based Simulation of Group Learning.- An Agent-Based Model That Relates Investment in Education to Economic Prosperity.- Economy, Trust and Reputation.- Trust-Based Inter-temporal Decision Making: Emergence of Altruism in a Simulated Society.- Multi-agent Model of Technological Shifts.- Beyond Accuracy. Reputation for Partner Selection with Lies and Retaliation.

REPUTATION FOR INNOVATING SOCIAL NETWORKS

Reputation is a fundamental instrument of partner selection. Developed within the domain of electronic auctions, reputation technology is being been imported by other applications, from social networks to institutional evaluation. Its impact on trust enforcement is uncontroversial and its management is of primary concern for entrepreneurs and other economic operators.In this paper, we will briefly report on simulation-based studies of the role of reputation as a more tolerant form of social capital than familiarity networks. Whereas the latter exclude nontrustworthy partners, reputation is a more inclusive mechanism on which larger and more dynamic networks are constructed. After the presentation of the theory of reputation developed by the authors in the last decade, a computational system (REPAGE) for forming and exchanging reputation information will be presented and findings from experimental simulations recently run on this system will be resumed. Final remarks and ideas for future work will conclude the paper.

A Model of Social Organization and the Evolution of Food Sharing in Vampire Bats

This article is aimed at exploring the role of groups in the evolution of a well-known form of altruism: blood sharing among vampire bats. In particular, we are interested in the formation and maintenance of new social structures (roosts) from initial populations as a consequence of both demographic growth and social organization. The example of vampire bats is especially interesting because of the flexible roost-switching behavior shown by these animals in nature. The main hypothesis made in this article concerns the role of grooming networks in roost formation, and was investigated by means of simula tion grounded on ethological evidence. The use of simulation allows the discussion of generative hypotheses on the origin of roosts, which are emergent from individual behavior. Besides confirming the main expectations, the results point to the need for a natural ordering in grooming partner selection. This ordering can be obtained not only through kin-based groups but also through the maintenance of a non kin-based precedence rule.

Mechanism change in a simulation of peer review: from junk support to elitism

Peer review works as the hinge of the scientific process, mediating between research and the awareness/acceptance of its results. While it might seem obvious that science would regulate itself scientifically, the consensus on peer review is eroding; a deeper understanding of its workings and potential alternatives is sorely needed. Employing a theoretical approach supported by agent-based simulation, we examined computational models of peer review, performing what we propose to call redesign, that is, the replication of simulations using different mechanisms. Here, we show that we are able to obtain the high sensitivity to rational cheating that is present in literature. In addition, we also show how this result appears to be fragile against small variations in mechanisms. Therefore, we argue that exploration of the parameter space is not enough if we want to support theoretical statements with simulation, and that exploration at the level of mechanisms is needed. These findings also support prudence in the application of simulation results based on single mechanisms, and endorse the use of complex agent platforms that encourage experimentation of diverse mechanisms.

Social cognitive factors of unfair ratings in reputation reporting systems

We will concentrate on the potential of reputation for optimising electronic transactions, liable to fraud and cheating. No surprise, electronic auctions have been the first arena for the implementation of computerised reputation systems. Economists expect that the probability of cooperation is positively affected by online reputation reporting systems (e.g., eBay), but electronic communities present several opportunities and forms of misbehaving also at the level of reputation. In eBay, rated transactions are about 50% of the total and positive ratings exceed negative ones. This evidence is interpreted in terms of a social cognitive model of reputation, allowing formulating testable hypotheses about the different performances of different reputational systems.

False reputation in social control

A simulation study is conduced on the spread of reputation in mixed respectful-cheater population. The effects of various mechanism giving raise to false reputation are shown, together with a discussion of foreseen results. The actual results of the simulation are then presented; informational accuracy is found to be an essential condition to maintain an advantage for the norms-followers.

Towards Reputation Enhanced Electronic Negotiations for Service Oriented Computing

Electronic commerce mechanisms are mainly investigated in two independent research areas: service-oriented computing (SOC) and multi-agent systems. The former as a means to deliver electronic services of various granularity and the latter as a testbed of electronic negotiation mechanisms. However, both research areas heavily rely on each other. On the one hand, service-oriented architectures need to support dynamic cooperation, negotiation, and adaptive interactions between offered services. On the other hand SOC represents a promising application for software agent technologies as a paradigm for electronic negotiations which future service economies will more and more rely on. Apart from the high flexibility and efficiency of such service economies, problems similar to the ones in real world economies will arise, such as the trusting problem between market participants. In this paper, we investigate the efficiency of reputation concepts in different negotiation protocols for electronic service economies. Based on social science findings we deduct hypotheses on the applicability of such mechanisms in various electronic negotiation settings.