Urban parking space reservation through bottom-up information provision: An agent-based analysis

The aim of this paper is to study the impacts of a reservation system for on-street parking. Such a system provides drivers looking for on-street parking with information on available parking spaces, thereby possibly reducing the need to cruise for parking and the accompanying negative externalities. The performance of the proposed system is studied using a highly detailed spatial agent-based simulation. The results of the simulations show that users of a reservation system benefit in terms of reduced search time and reduced walking distance under virtually all simulated circumstances. However, societal benefits are not as clear-cut. The benefit in search time for the users of the system comes at a cost to the regular drivers, which see a nearly identical increase in search time. In contrast, the positive impact on walking distance hardly influences walking distance for regular drivers. Hence, we conclude that the introduction of a reservation system for on-street parking results in a more efficient distribution of available parking spaces among drivers searching for parking.     

Dynamic parking negotiation and guidance using an agent-based platform

Modern prosperous cities strongly need advanced parking assistant systems, intelligent transportation systems providing drivers with parking information. Existing parking information systems usually ignore the parking price factor and do not automatically provide optimal car parks matching drivers’ demand. Currently, the parking price has no negotiable space; consumers lose their bargaining position to obtain better and cheaper parking. This study uses an intelligent agent system, and considering negotiable parking prices, selects the optimal car park for the driver. The autonomous coordination activities challenge traditional approaches and call for new paradigms and supporting middleware. An agent-based coordination network is proposed to bring true benefit to drivers and car park operators. These modern intelligent agents have capabilities including planning, mobility, execution monitoring and coordination. These properties can be used to construct the integrated parking assistant system.     

MamMoeT: An intelligent agent-based communication support platform for multimodal transport

In this paper, an intelligent agent-based communication support platform for multimodal transport is developed. The rationale for doing so is found in the potential of such a system to increase cost efficiency, service and safety for different transport-related actors. Although, at present several comparable systems exist, their current implementation is far from successful because of technological and economic obstacles. The new expert communication platform put forward here (called MamMoeT) addresses these two issues by using a software agent-based approach. Software agents are pieces of software representing a single user. They are autonomous, communicative and intelligent. The MamMoeT system developed can be described as a real-time decision support system in which intelligent software agents handle communicative tasks, exchange desired amounts of information among different users using common exchange protocols which act as translators between different systems.     

An approximation analysis for safety messages transmission in vehicle-to-vehicle WAVE networks

Wireless Access in the Vehicular Environment (WAVE) specification defines the WAVE Short Message Protocol (WSMP) for delivering WAVE Short Messages (WSMs). In the multihop transmission, WSMs are first received and stored in queues and then forwarded to the next hop. Unfortunately, WSMP does not specify any mechanism to avoid the messages loss resulted from queueing overflow. In this paper, a dual threshold-based queueing management which adjusts the message accepting rate upon the current queue length is proposed. The multihop transmission can be modeled as a tandem queueing network, and a discrete time Markov chain (DTMC) can be applied to evaluate the proposed queueing management. Since the computational complexity increases with the number of hops, an approximation approach to resolve DTMC model is also presented. Simulation results demonstrate the accuracy of approximation and the effectiveness of the proposed queueing management.     

An agent-based cognitive mapping system for sales opportunity analysis

The cognitive map (CM) is a representation of the causal relationships existing among the decision elements of a given object and/or problem, and also describes experts’ tacit knowledge. The CM has proven particularly useful in solving unstructured problems with many variables and causal relationships. Taking into consideration the amount of CM application studies thus far conducted in various fields, there has been relatively little research focused on the process of developing a CM. There have been some studies concerning the CM design process, most notably those conducted by Nelson, Nadkarni, Narayanan, and Ghods (2000) and Annibal, Tatiana, Susan, Julie, and Arthur (2006); however, these have failed to come up with a systematic approach in terms of the essential CM elements, which include: (1) the number of nodes, (2) the cause-and-effect relationships (arrows) among nodes, and (3) the strength of the cause-and-effect relationships (causality coefficients). The principal objective of this study, then, was to, first, determine the number of nodes that constitute a CM; second, to extract the cause-and-effect relationships among the nodes; and third, to devise an objective and systematic approach by which the causality coefficient within a single framework can be obtained. To accomplish this objective, our study adopts a CM-based mechanism referred to as the agent-based cognitive mapping system (ABCMS). Moreover, in order to extract effectively the three key elements of a CM, this study introduces the concepts of the multi-agent system (MAS) and particle swarm optimization (PSO), which allow for the construction of an ABCMS with a flexible and dynamic mechanism.     

Automatic price negotiation on the web: An agent-based web application using fuzzy expert system

A traditional internet auction is restricted by the limitation of time. It is necessary to conduct an internet auction in a certain time period. The final trading price is determined until this certain period ends. This study improves this situation by removing the time limitation. Based on the fuzzy inference theory, this paper proposes an agent-based price negotiation system for on-line auctions. Mainly, three agents are used in the study: a seller agent, a buyer agent, and a mediator agent. The proposed system provides an easy-to-use environment and good customizability for users (buyers or sellers) to customize their price negotiation strategies using user-defined fuzzy rules. The final negotiated price is immediately determined after the buyer sends his bids to the proposed system. This study develops a Java-based computer package to implement the price negotiation system where Model-View-Controller (MVC) design pattern is employed in design of the package. Unified Modeling Language (UML) is also utilized to describe the structures and behaviors of the package. To validate the proposed system, this study built an on-line auction website with the proposed price negotiation mechanism for internet users to buy or sell their merchandises. An evaluation was finally conducted to investigate the users’ satisfaction with the proposed system.Briefly, the proposed system is featured by: (1) instantly getting negotiated price without waiting; (2) conducting price negotiation at any time; (3) determining strategy rules easily, and (4) using customizable negotiation strategies defined by users.     

An agent-based English auction protocol using Elliptic Curve Cryptosystem for mobile commerce

Rapid development of the Internet and the extensive use of mobile phones have increased demand for mobile devices in Internet auctions. This trend is acting as an incentive to develop an auction model for mobile-based environment. Recently, Kuo-Hsuan Huang proposed a mobile auction agent model (MoAAM), which allows the bidders to participate in online auctions through a mobile agent. He used modular exponentiation operations in his method. As a result, the processing time for key generation, bidding, and verification were long. Thus, we propose to add the concept of Elliptic Curve Cryptosystem (ECC) onto MoAAM, because ECC has low computation amount and small key size, both of which will aid to increase the speed in generating keys, bidding, and verification. In terms of reduction of computation load on mobile devices and auction-manager server, the proposed method will make online auction system more efficient as well as more convenient to use. This paper mainly uses the English auction protocol as the key auction protocol. The protocol consists of four entities: Registration Manager (RM), Agent House (AH), Auction House (AUH), and Bidders (B). The Registration Manager registers and verifies Bidder identity. The Agent House manages the agents and assigns public transaction keys to Bidders. The Auction House provides a place for auction and maintains all necessary operations for a smooth online auction. Bidders are buyers who are interested in purchasing items at the auction. Our proposed method conforms to the requirements of an online auction protocol in terms of anonymity, traceability, no framing, unforgetability, non-repudiation, fairness, public verifiability, unlinkability among various auction rounds, linkability within a single auction round, efficiency of bidding, one-time registration, and easy revocation.     

Automating user reviews using ontologies: an agent-based approach

The Web is becoming a global market place, where the same services and products are offered by different providers. When obtaining a service, consumers have to select one provider among many alternatives to receive a service or buy a product. In real life, when obtaining a service, many consumers depend on the user reviews. User reviews—presumably written by other consumers—provide details on the consumers’ experiences and thus are more informative than ratings. The down side is that such user reviews are written in natural language, making it extremely difficult to be interpreted by computers. Therefore, current technologies do not allow automation of user reviews and require too much human effort for tasks such as writing and reading reviews for the providers, aggregating existing information, and finally choosing among the possible candidates. In this paper, we represent consumers’ reviews as machine processable structures using ontologies and develop a layered multiagent framework to enable consumers to find satisfactory service providers for their needs automatically. The framework can still function successfully when consumers evolve their language and when deceptive reviewers enter the system. We show the flexibility of the framework by employing different algorithms for various tasks and evaluate them for different circumstances.     

DPP: An agent-based approach for distributed process planning

A changing shop floor environment characterized by larger variety of products in smaller batch sizes requires creating an intelligent and dynamic process planning system that is responsive and adaptive to the rapid adjustment of production capacity and functionality. In response to the requirement, this research proposes a new methodology of distributed process planning (DPP). The primary focus of this paper is on the architecture of the new process planning approach, using multi-agent negotiation and cooperation. The secondary focus is on the other supporting technologies such as machining feature-based planning and function block-based control. Different from traditional methods, the proposed approach uses two-level decision-making—supervisory planning and operation planning. The former focuses on product data analysis, machine selection, and machining sequence planning, while the latter considers the detailed working steps of the machining operations inside of each process plan and is accomplished by intelligent NC controllers. By the nature of decentralization, the DPP shows promise of improving system performance within the continually changing shop floor environment.     

An automatic parking system using an optimized image-based fuzzy controller by genetic algorithms

An automatic parking system of a car-like mobile robot is an important issue in commercial applications. An image-based fuzzy controller for an automatic parking system of a car-like mobile robot was developed in previous work, where the membership functions were tuned by experimentally. The aim of this paper is to optimize the parameters of the membership functions, which were performed in previous work, using a genetic algorithm against the complicated tuning of the controller. The details of GA implementation, such as the design parameters and choice of fitness function, are described. Simulation results illustrate the effectiveness of the developed schemes.     

Virtual team meetings: An analysis of communication and context

We report a simulation study of virtual team meetings. Participants role-played companies collaborating on a design problem while supported by a range of IT tools, such as videoconferencing and shared applications. Meetings were analysed to investigate how sharing computing facilities, operating the technology, and company status, influenced communications. Significantly more talk occurred in larger teams where participants shared I.T. facilities BUT this extra talk was restricted to talk within a single location. No extra talk was shared across the virtual team via the communications link. Where facilities were shared, technology controllers dominated cross-site talk. To encourage free communication across distributed virtual teams we recommend providing each participant with their own communications facility even if this is technologically less advanced than if technology support were shared.     

ABSEM: An agent-based simulator of emotions in mindfulness programs

Among other utilities, expert and intelligent systems can provide estimations similar to the ones from human experts. In this context, agent-based simulators support the prediction of some features of groups of individuals based on the simulation of some autonomous entities called agents. However, the literature lacks the appropriate simulators to simulate the repercussions of mindfulness programs on the emotions of meditators. Mindfulness has proven to be related to several indicators of health and quality of life in the later years. Mindfulness has also proven to be strongly related with certain emotions, but there are different programs for training mindfulness. In this context, the current approach presents an Agent-based Simulator of Emotions in Mindfulness programs (ABSEM). The current approach allows instructors to define different mindfulness programs and simulate their repercussions on the emotions of a group of practitioners with certain features. In this way, these simulations support instructors in selecting an adequate program for a given group of practitioners. In addition, this simulator can also be useful for practitioners because it lets them know an estimation of the repercussions of each mindfulness program. In two different scenarios, the experiments show that the system provides simulated outcomes that are similar to the real ones, when establishing the same input circumstances. The current work distributes ABSEM as an open-source tool. This fact not only assures the reproducibility of the experiments, but also allows researchers and practitioners to use and extend the simulator. Therefore, ABSEM contributes on the application of expert and intelligent systems to the mindfulness field, allowing novel instructors and meditators benefit from the implicit knowledge integrated in the simulator. This system can promote both (a) the use of expert systems for exploring their performance in predicting emotional repercussions from any kind of health intervention, and (b) the practice of mindfulness for repairing negative emotions as a social benefit.     

On-line student debate: An experiment in communication using computer Networks

A one-month experiment in man-computer-man communication using the Pitt time-sharing system and the SRI system in the ARPA Network is described. Thirteen graduate students in computer science served as experimental subjects, carrying out limited, pairwise debates on a selected set of controversial topics, with subsequent on-line critique. Besides studying the feasibility of this technique, the main purpose was to probe into the significance (if any) attributed by human communicators to the structure of files used for communicating information. Comparative systems performance and various user characteristics were also observed. Student reactions and other recorded data are interpretively discussed and summarized.     

ACCESS: An agent-based model to explore job accessibility inequalities

This paper presents ACCESS, an agent-based model for exploring job accessibility inequalities among different social groups. ACCESS allows for investigation on the impact of public transport and land use policies on the residential location of the working population and their accessibility to job opportunities. ACCESS can be adapted to different realities, allowing to represent societies with diverse socioeconomic disparities. A utility function composed of job accessibility and neighborhood status is maximized by agents during the residential location choice process. The model outputs include Lorenz curves considering the accessibility dimension, as well as Gini metrics to support the analysis of interventions impacts on accessibility inequalities. An empirical case study is performed on the municipality of Sao Paulo, which is characterized by high levels of inequality. Five experiments were simulated considering three different socio-occupational groups. The first experiment includes (i) new public mass rail transport lines, and the other four experiments consider the new transport infrastructure from the first experiment and add (ii) new social housing location strategies; (iii) new job locations; (iv) new jobs and different social housing supplies and location strategies; and (v) provision of social housing based on a government housing program. The results show that ACCESS allowed the residential location of different social status groups to be depicted with a high correlation to the observed situation. Regarding the case study, the results indicate that only having interventions on transport system is insufficient to provide a significant change in terms of inequality. Better results that impact inequality are reached with public mass rail transport interventions associated with land use policies with different social housing and job location programs.     

An interactive image communication system using narrowband lines

A two-node network for interactive image communication, operating over 300 baud, switched telephone lines, has been developed and demonstrated. This system utilizes the concept of a common visual space where in an identical image is presented to all users. The image can be modified by any user, the results of which will be seen by all. Individual nodes can be either single- or dual-processor based. The latter configuration divides the load between a host processor, which executes the application and handles the communication to the other node, and a slave terminal processor, which provides the display capability and handles interrupts. A dual-processor arrangement provides flexibility in the choice of terminal, e.g. raster or random plotting. The slave terminal can be driven by any host computer which outputs information in a particular coded format called Graphical Task Instructions (GTI).     

Cooperative control and communication of intelligent swarms: a survey

Individuals exchange information, experience and strategy based on communication. Communication is the basis for individuals to form swarms and the bridge of swarms to realize cooperative control. In this paper, the multi-robot swarm and its cooperative control and communication methods are reviewed, and we summarize these methods from the task, control, and perception levels. Based on the research, the cooperative control and communication methods of intelligent swarms are divided into the following four categories: task assignment based methods (divided into market-based methods and alliance based methods), bio-inspired methods (divided into biochemical information inspired methods, vision based methods and self-organization based methods), distributed sensor fusion and reinforcement learning based methods, and we briefly define each method and introduce its basic ideas. Based on WOS database, we divide the development of each method into several stages according to the time distribution of the literature, and outline the main research content of each stage. Finally, we discuss the communication problems of intelligent swarms and the key issues, challenges and future work of each method.     

The garbage can model of organizational choice: An agent-based reconstruction

We reconstruct Cohen, March and Olsen’s original Garbage Can model of organizational choice as a multi-agent system. We show that while some of the original results might be viewed as artifacts of particular modeling choices, the basic insights of the original model are confirmed over a wide range of experimental conditions. The simulation experiments confirm and extend some of the most interesting conclusions of the Garbage Can model: most decisions are made without solving any problem, the few problems that are solved generally pertain to the lower hierarchical levels and, consequently, the members of an organization encounter the same old problems again and again.     

Driver-centred vehicle automation: using network analysis for agent-based modelling of the driver in highly automated driving systems

To the average driver, the concept of automation in driving infers that they can become completely ‘hands and feet free’. This is a common misconception, however, one that has been shown through the application of Network Analysis to new Cruise Assist technologies that may feature on our roads by 2020. Through the adoption of a Systems Theoretic approach, this paper introduces the concept of driver-initiated automation which reflects the role of the driver in highly automated driving systems. Using a combination of traditional task analysis and the application of quantitative network metrics, this agent-based modelling paper shows how the role of the driver remains an integral part of the driving system implicating the need for designers to ensure they are provided with the tools necessary to remain actively in-the-loop despite giving increasing opportunities to delegate their control to the automated subsystems.

Practitioner Summary: This paper describes and analyses a driver-initiated command and control system of automation using representations afforded by task and social networks to understand how drivers remain actively involved in the task. A network analysis of different driver commands suggests that such a strategy does maintain the driver in the control loop.     

Applications of agent-based systems in intelligent manufacturing: An updated review

Agent technology has been recognized as a promising paradigm for next generation manufacturing systems. Researchers have attempted to apply agent technology to manufacturing enterprise integration, enterprise collaboration (including supply chain management and virtual enterprises), manufacturing process planning and scheduling, shop floor control, and to holonic manufacturing as an implementation methodology. This paper provides an update review on the recent achievements in these areas, and discusses some key issues in implementing agent-based manufacturing systems such as agent encapsulation, agent organization, agent coordination and negotiation, system dynamics, learning, optimization, security and privacy, tools and standards.