USING INSTITUTIONS TO BRIDGE THE TRUST-GAP IN UTILITY COMPUTING MARKETS – AN EXTENDED “TRUST-GAME”

With the ongoing evolution of the Internet as a trading platform and the corresponding paradigm change from small non-anonymous markets to their large anonymous utility computing pendants, new challenges arise. One of them is the promotion of trust in these new markets as it is an essential prerequisite for bilateral economic exchange [2]. This work tries to meet this challenge by using an evolutionary game-theoretic approach in combination with institutions. Starting from a basic trust game it will show that the introduction of institutions will lead to the crowding in of trustworthy behavior, even if no special detection capabilities are available

Proceedings of the 11th European Agent Systems Summer School Student Session

This volume contains the papers presented at the Student Session of the 11th European Agent Systems Summer School (EASSS) held on 2nd of September 2009 at Educatorio della Providenza, Turin, Italy. The Student Session, organised by students, is designed to encourage student interaction and feedback from the tutors. By providing the students with a conference-like setup, both in the presentation and in the review process, students have the opportunity to prepare their own submission, go through the selection process and present their work to each other and their interests to their fellow students as well as internationally leading experts in the agent field, both from the theoretical and the practical sector. Table of Contents: Andrew Koster, Jordi Sabater Mir and Marco Schorlemmer, Towards an inductive algorithm for learning trust alignment . . . 5; Angel Rolando Medellin, Katie Atkinson and Peter McBurney, A Preliminary Proposal for Model Checking Command Dialogues. . . 12; Declan Mungovan, Enda Howley and Jim Duggan, Norm Convergence in Populations of Dynamically Interacting Agents . . . 19; Akın Günay, Argumentation on Bayesian Networks for Distributed Decision Making . . 25; Michael Burkhardt, Marco Luetzenberger and Nils Masuch, Towards Toolipse 2: Tool Support for the JIAC V Agent Framework . . . 30; Joseph El Gemayel, The Tenacity of Social Actors . . . 33; Cristian Gratie, The Impact of Routing on Traffic Congestion . . . 36; Andrei-Horia Mogos and Monica Cristina Voinescu, A Rule-Based Psychologist Agent for Improving the Performances of a Sportsman . . . 39; --Autonomer Agent,Agent,Künstliche Intelligenz

From real-world regulations to concrete norms for software agents: a case-based reasoning approach

When trying to use software agents (SAs) for real-world business and thereby putting them in a situation to operate under real-world laws, the abstractness of human regulations often poses severe problems. Thus, human regulations are written in a very abstract way, making them open to a wide range of interpretations and applicable for several scenarios as well as stable over a longer period of time. However, in order to be applicable for SAs, regulations need to be precise and unambiguous. This paper presents a case-based reasoning approach in order to bridge the gap between abstract human regulations and the concrete regulations needed for SAs, by developing and using a knowledge base that can be used for drawing analogies and thereby serves as reference for \translating" abstract terms in human regulations.(undefined

I-ABM:combining institutional frameworks and agent-based modelling for the design of enforcement policies

Computer science advocates institutional frameworks as an effective tool for modelling policies and reasoning about their interplay. In practice, the rules or policies, of which the institutional framework consists, are often specified using a formal language, which allows for the full verification and validation of the framework (e.g. the consistency of policies) and the interplay between the policies and actors (e.g. violations). However, when modelling large-scale realistic systems, with numerous decision-making entities, scalability and complexity issues arise making it possible only to verify certain portions of the problem without reducing the scale. In the social sciences, agent-based modelling is a popular tool for analysing how entities interact within a system and react to the system properties. Agent-based modelling allows the specification of complex decision-making entities and experimentation with large numbers of different parameter sets for these entities in order to explore their effects on overall system performance. In this paper we describe how to achieve the best of both worlds, namely verification of a formal specification combined with the testing of large-scale systems with numerous different actor configurations. Hence, we offer an approach that allows for reasoning about policies, policy making and their consequences on a more comprehensive level than has been possible to date. We present the institutional agent-based model methodology to combine institutional frameworks with agent-based simulations). We furthermore present J-InstAL, a prototypical implementation of this methodology using the InstAL institutional framework whose specifications can be translated into a computational model under the answer set semantics, and an agent-based simulation based on the jason tool. Using a simplified contract enforcement example, we demonstrate the functionalities of this prototype and show how it can help to assess an appropriate fine level in case of contract violations. © 2013 Springer Science+Business Media Dordrecht