Locating Agents in RFID Architectures

The use of software agents can create an “intelligent” interface between users’ preferences and the back‐end systems. Agents are now able to interact and communicate with each other, forming a virtual community and feeding back the user with suggestions. Innovative systems related to Asset Tracking, Inventory and Shelving architectures are more often involving advanced communication techniques (e.g., RFID); these systems are responsible for user authentication and objects verification. RFID systems could have jamming situations where many objects are moving at the same time and in the same direction. Moreover, other disadvantages have also been observed, such as hindering further implementations, privacy and security issues problems, in addition to the system’s disruptive behavior in case of crowd checkouts (e.g., Supermarket and Airports). Addressing these disadvantages, this paper proposes a possible integration between a Multi‐Agent framework and an RFID‐based application (back‐end). This integration would allow objects (such as passports or goods) with RFID tags to better check‐out through airports or supermarket gates that contain RFID‐readers

Smart Ride Seeker (SRS) An Introductory Plan

A diverse range of architectures and concepts was proposed by scholars within the theme of Car Pooling Problem solving. Most of these scholars have attempted to put together two major elements: the need for people to move from a place to another, and the resources used to accomplish this action. Based on the use of location and available car seats, Car sharing systems allowed a substantial number of people to share car rides. These systems would, among other advantages, rationalize energy consumption, save money, and decrease traffic jams and human stress, and eventually make a significant improvement in human life. This paper proposes the initial phase of Smart Ride Seeker (SRS), which is a Car Pooling-like technique for distributing resources among a community that shares the same goals. This SRS technique will be developed through a mobile-based application that allows the mapping of ride seekers’ locations along with the locations of available cars on a graphical interface/map, giving the possibility to calculate the fastest and simplest path for both the ride giver and seeker to meet and fulfill their demand

ToothAgent: Brushing on Your Behalf

Common interests among people in different communities and levels are driving plenty of research groups and industry developers to pay more attention to such a vast zone of opportunities. Nowadays, unifying service architectures and implementations has become achievable, advanced and sophisticated mobile services early-adopters and late-integrators are standing over one tangible concept; trouble-free life throughout hassle-free services, system design flexibility and support is established through superior and refined research methodologies and techniques. In this paper, we introduce a new form of previously implemented architecture: ToothAgent, we perform a simple amplification process that helps concatenating ToothAgent newly proposed schemes. We confirm a possible augmentation then we demonstrate the foreseen architecture possible integrations

Sweeper-Agent Recommendations-Tree Early Scheme

This paper presents a possible roadmap for what we call a “Sweeper-Agent”: an environment-friendly agents-based mobile technique, which is carried out within the activities of BlueAgents, a newly-formed research project focusing on the integration of mobile Bluetooth communications and Agent-based applications. We foresee an architecture of a service management technique that would increase the efficiency of mobile service. This paper proceeds in four sections. The first section outlines the state of the art of Agent-Oriented Architectures, and the motivation behind our research. The next section explains the Sweeper-Agent framework that uses Agent-Based Recommendations-Tree for mobile application, and how this will help mobile applications developers. Then we introduces Sweeper-Agent foreseeable integrations. And we describes the Sweeper-Agent positioning within the already implemented ToothAgent. Finally, we demonstrates the value-added service opportunities that may occur when Sweeper-Agent is implemented within a mobile-agent architecture

ANDIAMO: A Multiagent System to Provide a Mobile-based Rideshare Service

A diverse range of architectures and concepts has been proposed by scholars within the theme of Car Pooling. Most of these studies have attempted to tie together two major elements: the need for people to move from a place to another, and the resources used to accomplish this action. Based on the use of location and available car seats, Rideshare systems allow a substantial number of people to share car rides. These systems would, among other advantages, rationalize energy consumption, save money, and decrease traffic jams and human stress, and eventually make a significant improvement in human life. However, system accessibility has prevented these architectures from being widely reached. In this paper, we present an agent-based Rideshare system that is accessible via lightweight devices (mobile phones and PDAs), where Bluetooth technology is adopted to reflect users’ locality. The paper illustrates the overall infrastructure of the system, the specific protocols it uses, and the algorithms that it implements to recognize the Multiagent System (MAS) negotiations

Semi-Heuristic Negotiation Protocol for Agent-based Mobile Service Application

This article has been submitted for publication outside of the Department of Information and Communication Technology (DIT) – University of Trento, and will probably be copyrighted if accepted for publication. It has been issued as a Research Technical Report for early dissemination of its contents. In view of the transfer of copyright to the outside publisher, its distribution outside of DIT prior to publication should be limited to peer communications and specific requests. After outside publication, requests should be filled only by reprints or legally obtained copies of the article. In this paper we present a new negotiation protocol that assists multi-agent systems to differently approach the achievement of complex tasks. In particular, we narrow our research scope to focus on the situation where a multi-agent system is serving lightweight devices through advanced communication methods (e.g., Bluetooth). Like many other schemes, our model provides agents with a monetary system and a mechanism for feedback calculation. We aim at accelerating agent’s interactions while resolving end-user composite tasks. Once its efficiency is proven, our protocol can be integrated in a scenario where multipart mobilebased services are offered to holders of lightweight devices

Design Patterns to Enable Agent-based Mobile Service Application Development.

This paper proposes a new framework to develop agent-based mobile phones service application using the current constructions derived from agent patterns approaches. Agent patterns are categorized in technically various modules that interconnect according to the users’ demands and application needs. Our framework, applying a multi-agent systems technique, allows users to drag and drop certain system plug-ins to enable explicit functions; this will shape the final behavior of agents within the application and determine its characteristics. We provide an example of a real-life application to illustrate the implementation of this framework

A Nomadicity-driven Negotiation Protocol, Tactics and Strategies for Interacting Software Agents.

The rising integration of pocket computing devices in our daily life duties has taken the attention of researchers from different scientific backgrounds. Today's amount of software applications that bring together advanced mobile services and literature of Artificial Intelligence (AI) is quite remarkable and worth investigating. Cooperation, coordination and negotiation are some of AI's focal points wherein many of its related research efforts are strengthening the join between sophisticated research outcomes and modern life requirements, such as serviceability on the move. In Distributed Artificial Intelligence (DAI), several of the research conducted in Multi-Agent Systems (MASs) addresses the mutually beneficial agreements that a group of interacting autonomous agents are expected to reach. In our research, we look at agents as the transportable software packets that each represents a set of needs a user of a pocket computing device demands from a remote service acquisition platform. However, when a set of software agents attempt to reach an agreement, a certain level of cooperation must be reached first, then, a negotiation process is carried out. Depending on each agent's negotiation skills and considerations, the returns of each accomplished agreement can either be maximized or minimized. In this thesis, we introduce a new negotiation model, (i.e., protocol, set of tactics, strategy), for software agents to employ while attempting to acquire a service on behalf of users of pocket computing devices. The purpose of our model is to maximize the benefits of the interacting agents while considering the limitations of the communication technologies involved and, the nomadic nature of the users they represent. We show how our model can be generically implemented. Then, we introduce two case-studies that we have been working on with our industrial partner and, we demonstrate these cases' experimental results before and after applying our negotiation model