An E-Business Model Facilitating Service Provider Selection in B2C E-Commerce

The advent and expansion of the Internet and its applications, among them e-commerce, has provided new opportunities for the emergence of novel e-business models. A portion of these models are in the form of performing a mediatory role to provide some services for customers or businesses, and to facilitate transactions between them. In B2C e-commerce, often, a service consumer may supply his service demand from a range of providers and when he doesn\u27t have any transaction with many of them making an accurate decision becomes challenging. Therefore, he would need to interact with others to acquire relevant information. Current approaches for addressing this issue are generally rating-based and perform poorly. Recently, an experience-based approach has been proposed by ensoy et al [1]. This paper reviews this approach, analyzes its weaknesses and problems and proposes a new model to eliminate those problems, in which a third party assists the consumers in choosing their desired service providers

Obligation Norm Identification in Agent Societies

Most works on norms have investigated how norms are regulated using institutional mechanisms. Very few works have focused on how an agent may infer the norms of a society without the norm being explicitly given to the agent. This paper describes a mechanism for identifying one type of norm, an obligation norm. The Obligation Norm Inference (ONI) algorithm described in this paper makes use of an association rule mining approach to identify obligation norms. Using agent based simulation of a virtual restaurant we demonstrate how an agent can identify the tipping norm. The experiments that we have conducted demonstrate that an agent in the system is able to add, remove and modify norms dynamically. An agent can also flexibly modify the parameters of the system based on whether it is successful in identifying a norm.Norms, Social Norms, Obligations, Norm Identification, Agent-Based Simulation, Simulation of Norms, Artificial Societies, Normative Multi-Agent Systems (NorMAS)

Saliency Map for Visual Perception

Human and other primates move their eyes to select visual information from the scene, psycho-visual experiments (Constantinidis, 2005) suggest that attention is directed to visually salient locations in the image. This allows human beings to bring the fovea onto the relevant parts of the image, to interpret complex scenes in real time. In visual perception, an important result was the discovery of a limited set of visual properties (called pre attentive), detected in the first 200-300 milliseconds of observation of a scene, by the low-level visual system. In last decades many progresses have been made into research of visual perception by analyzing both bottom up (stimulus driven) and top down (task dependent) processes involved in human attention. Visual Saliency deals with identifying fixation points that a human viewer would focus on the first seconds of the observation of a scene

Trust and reputation management in decentralized systems

In large, open and distributed systems, agents are often used to represent users and act on their behalves. Agents can provide good or bad services or act honestly or dishonestly. Trust and reputation mechanisms are used to distinguish good services from bad ones or honest agents from dishonest ones. My research is focused on trust and reputation management in decentralized systems. Compared with centralized systems, decentralized systems are more difficult and inefficient for agents to find and collect information to build trust and reputation. In this thesis, I propose a Bayesian network-based trust model. It provides a flexible way to present differentiated trust and combine different aspects of trust that can meet agents’ different needs. As a complementary element, I propose a super-agent based approach that facilitates reputation management in decentralized networks. The idea of allowing super-agents to form interest-based communities further enables flexible reputation management among groups of agents. A reward mechanism creates incentives for super-agents to contribute their resources and to be honest. As a single package, my work is able to promote effective, efficient and flexible trust and reputation management in decentralized systems

Metacognizione, attenzione e intelligenza emotiva: uno studio sperimentale

Il tema dell'intelligenza emotiva è piuttosto attuale e dibattuto all'interno del panorama scientifico della psicologia moderna. In generale, c'è unanimità nel definire l'intelligenza emotiva come la capacità di riconoscere le emozioni proprie e altrui in modo da poter strutturare e regolare adeguate relazioni sociali

Emergent Properties of Referral Systems

Agents must decide with whom to interact, which is nontrivial when no central directories are available. A classical decentralized approach is referral systems, where agents adaptively give referrals to one another. We study the emergent properties of referral systems, especially those dealing with their quality, efficiency, and structure. Our key findings are (1) pathological graph structures can emerge due to some neighbor selection policies and (2) if these are avoided, quality and efficiency depend on referral policies. Further, authorities emerge automatically and the extent of their relative authoritativeness depends on the policies