Showing papers in "IEEE Intelligent Systems in 2011"
TL;DR: The advantages and disadvantages of crowdsourcing applications applied to disaster relief coordination are described and several challenges must be addressed to make crowdsourcing a useful tool that can effectively facilitate the relief progress in coordination, accuracy, and security.
Abstract: This article briefly describes the advantages and disadvantages of crowdsourcing applications applied to disaster relief coordination. It also discusses several challenges that must be addressed to make crowdsourcing a useful tool that can effectively facilitate the relief progress in coordination, accuracy, and security.
817 citations
TL;DR: The paper mentions that a hybrid recommender systems framework creates user-profile groups before applying a collaborative-filtering algorithm by incorporating techniques from the multiple-criteria decision-analysis field.
Abstract: The paper mentions that a hybrid recommender systems framework creates user-profile groups before applying a collaborative-filtering algorithm by incorporating techniques from the multiple-criteria decision-analysis (MCDA) field.
171 citations
TL;DR: Describes the Wings intelligent workflow system that assists scientists with designing computational experiments by automatically tracking constraints and ruling out invalid designs, letting scientists focus on their experiments and goals.
Abstract: Describes the Wings intelligent workflow system that assists scientists with designing computational experiments by automatically tracking constraints and ruling out invalid designs, letting scientists focus on their experiments and goals.
170 citations
TL;DR: A new methodology integrated in MASCEM for bid definition in electricity markets is proposed, which uses reinforcement learning algorithms to let players perceive changes in the environment, thus helping them react to the dynamic environment and adapt their bids accordingly.
Abstract: To study and understand this type of market, we developed the Multiagent Simulator of Competitive Electricity Markets (MASCEM) platform based on multiagent simulation. The MASCEM multiagent model includes players with strategies for bid definition, acting in forward, day-ahead, and balancing markets and considering both simple and complex bids. Our goal with MASCEM was to simulate as many market models and player types as possible. This approach makes MASCEM both a short and medium term simulation as well as a tool to support long-term decisions, such as those taken by regulators. This article proposes a new methodology integrated in MASCEM for bid definition in electricity markets. This methodology uses reinforcement learning algorithms to let players perceive changes in the environment, thus helping them react to the dynamic environment and adapt their bids accordingly.
152 citations
TL;DR: The history of the development of traffic control and management systems within the evolving computing paradigm is reviewed and the state of traffic Control and Management systems based on mobile multiagent technology is shown.
Abstract: Agent-based traffic management systems can use the autonomy, mobility, and adaptability of mobile agents to deal with dynamic traffic environments. Cloud computing can help such systems cope with the large amounts of storage and computing resources required to use traffic strategy agents and mass transport data effectively. This article reviews the history of the development of traffic control and management systems within the evolving computing paradigm and shows the state of traffic control and management systems based on mobile multiagent technology.
149 citations
TL;DR: The article provides a preliminary account of the operational process of command and control based on the cyber-physical-social system (CPSS) and a self-synchronization mechanism and connects the physical network, cyberspace, mental space, and social network.
Abstract: The article provides a preliminary account of the operational process of command and control based on the cyber-physical-social system (CPSS) and a self-synchronization mechanism. The proposed CPSS for command and control incorporates the essential characteristics of operational mechanism and connects the physical network, cyberspace, mental space, and social network.
139 citations
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TL;DR: This special issue presents some of the best works being developed worldwide that deal with the new challenges of BI from an intelligent systems perspective.
Abstract: Brain informatics (BI) is an emerging interdisciplinary and multidisciplinary research field that focuses on studying the mechanisms underlying the human information processing system. BI investigates the essential functions of the brain, ranging from perception to thinking, and encompassing such areas as multiperception, attention, emotion, memory, language, computation, heuristic search, reasoning, planning, decision making, problem solving, learning, discovery, and creativity. This special issue presents some of the best works being developed worldwide that deal with the new challenges of BI from an intelligent systems perspective.
95 citations
TL;DR: The paper is discussing well-known trust enhanced information filtering techniques for recommending controversial reviews by the recommender systems.
Abstract: The paper is discussing well-known trust enhanced information filtering techniques for recommending controversial reviews by the recommender systems.
91 citations
TL;DR: Advances in neuroelectric recordings and computational tools allow investigation of interactive brain activity and connectivity in a group of subjects engaged in social interactions.
Abstract: Advances in neuroelectric recordings and computational tools allow investigation of interactive brain activity and connectivity in a group of subjects engaged in social interactions.
86 citations
TL;DR: The recent availability of massive amounts of networked data generated by email, instant messaging, mobile phone communications, micro blogs, and online social networks is enabling studies of population-level human interaction on scales orders of magnitude greater than what was previ ously possible as mentioned in this paper.
Abstract: The recent availability of massive amounts of networked data generated by email, instant messaging, mobile phone communications, micro blogs, and online social networks is enabling studies of population-level human interaction on scales orders of magnitude greater than what was previ ously possible.1'2 One important goal of applying statistical inference techniques to large networked datasets is to understand how behavioral conta gions spread in human social networks. More pre cisely, understanding how people influence or are influenced by their peers can help us understand the ebb and flow of market trends, product adoption and diffusion, the spread of health behaviors such as smoking and exercise, the productivity of information workers, and whether particular indi viduals in a social network have a disproportion ate amount of influence on the system.
84 citations
TL;DR: To help people live better in today's digitally explosive environment, the authors envision a Cyber-Individual (Cyber-I) that is the counterpart of a real individual in the physical world.
Abstract: To help people live better in today's digitally explosive environment, the authors envision a Cyber-Individual (Cyber-I) that is the counterpart of a real individual in the physical world.
TL;DR: This article presents five trade-offs identified to date that define boundary conditions on all macrocognitive work systems and illustrates how the known empirical generalizations about the performance of human work systems can be systematically organized by theTrade-offs.
Abstract: Articulating the laws of cognitive work has been a continuing theme in this department. A number of the articles represent an effort to move toward a unified theory of "macrocognitive work systems." These are complex adaptive systems designed to support near-continuous interdependencies among humans and intelligent machines to carry out functions such as sensemaking, replanning, mental projection to the future, and coordination. The effort to identify empirical generalizations and use them to construct a formal theory has led us to the identification of a number of fundamental trade-offs that place boundary conditions on all macrocognitive work systems. This article presents five trade-offs identified to date that define these boundary conditions. It also illustrates how the known empirical generalizations about the performance of human work systems can be systematically organized by the trade-offs.
TL;DR: The notion of coactive design is introduced, an approach to human-machine interaction that takes interdependence as the central organizing principle among people and agents working together as a team.
Abstract: This article discusses that the concept of levels of autonomy is incomplete and insufficient as a model for designing complex human-machine teams, largely because it does not sufficiently account for the interdependence among their members. Building on a theory of joint activity, we introduce the notion of coactive design, an approach to human-machine interaction that takes interdependence as the central organizing principle among people and agents working together as a team.
TL;DR: Incorporating affective characteristics (such as personality, emotion, and mood) in an agent-based group decision-support system can help improve the negotiation process.
Abstract: Incorporating affective characteristics (such as personality, emotion, and mood) in an agent-based group decision-support system can help improve the negotiation process.
TL;DR: Technical advances in the neuroelectric recordings and in the computational tools for the analysis of the brain activity and connectivity make it now possible to follow and to quantify, in real time, the interactive brain activity in a group of subjects engaged in social interactions.
Abstract: Technical advances in the neuroelectric recordings and in the computational tools for the analysis of the brain activity and connectivity make it now possible to follow and to quantify, in real time, the interactive brain activity in a group of subjects engaged in social interactions. The degree of interaction between persons can then be assessed by "reading" their neuroelectric activities. Imaging the social brain can thus open a new area of study in neuroscience.
TL;DR: Stealing-reality attacks attempt to steal social network and behavioral information through data collection and inference techniques, making them more dangerous than other types of identity theft.
Abstract: Stealing-reality attacks attempt to steal social network and behavioral information through data collection and inference techniques, making them more dangerous than other types of identity theft.
TL;DR: It is demonstrated that a randomized route-selection strategy resulting from a normal two-player game formulation of the transit problem can decrease the number of attacks and the payoff accumulated by pirates.
Abstract: Agent-based techniques have the potential to improve the security of international maritime transport threatened by a steep rise of maritime piracy. We have demonstrated that a randomized route-selection strategy resulting from a normal two-player game formulation of the transit problem can decrease the number of attacks and the payoff accumulated by pirates. Coordinating the movement of patrol and transit vessels without a central authority requires techniques for semi-cooperative planning and coalition formation. With regard to existing applications of agent-based techniques, the maritime domain seems currently under-represented compared to other traffic and transportation domains. This work is a first step in addressing the situation and bringing this important domain into the focus of researchers in the multiagent systems field.
TL;DR: The article explains the advantages of cloud computing and GPUs and presents the architectures of GPU-based cloud computing for transportation systems.
Abstract: The article focuses on the C part of the ACP approach. The ACP approach comprises of artificial societies, computational experiments, and parallel execution of real and artificial systems. It explains the advantages of cloud computing and GPUs and presents the architectures of GPU-based cloud computing for transportation systems.
TL;DR: This Guest Editors' Introduction identifies an opportunity for the cross-fertilization between power systems and energy markets researchers and new developments of AI.
Abstract: This Guest Editors' Introduction identifies an opportunity for the cross-fertilization between power systems and energy markets researchers and new developments of AI. The articles selected for this special issue provide the state-of-the-art information about research being conducted using AI in power systems and energy markets.
TL;DR: Using the two main approaches to security-oriented event analysis, explicit event recognition and anomaly detection, the authors attempt to semantically interpret video sequences to detect anomalous, dangerous, or forbidden situations.
Abstract: Using the two main approaches to security-oriented event analysis, explicit event recognition and anomaly detection, the authors attempt to semantically interpret video sequences to detect anomalous, dangerous, or forbidden situations.
TL;DR: A genetic algorithms and fuzzy programming methodology can help determine the minimum number of meters needed to monitor voltage sags and swells in power networks and identifies the buses on which those meters should be installed.
Abstract: A genetic algorithms and fuzzy programming methodology can help determine the minimum number of meters (and their location) needed to monitor voltage sags and swells in power networks. This paper proposes a methodology that determines the minimal number of power-quality meters needed to monitor a power network and identifies the buses on which those meters should be installed.
TL;DR: The paper presents a novel parallel system for URT operations that uses the concept of parallel system and computational experiments based on artificial systems (ACP) to analyze and facilitate passenger-flow management, vehicle scheduling, and other operational issues while considering human-related, environmental, andother social and economical factors.
Abstract: Urban rail transportation (URT) has long become the preferred public transportation choice for major metropolitan areas such as New York, London, Paris, Moscow, Tokyo, and Beijing. The highest daily record for Beijing's URT reached 5.71 million passenger trips in 2010, which makes the network extremely crowded in rush hours. To accommodate the increasing demand for URT, the service frequencies have been increased tremendously. To address these safety, efficiency, and reliability issues, the paper presents a novel parallel system for URT operations that uses the concept of parallel system and computational experiments based on artificial systems (ACP). The parallel URT system can analyze and facilitate passenger-flow management, vehicle scheduling, and other operational issues while considering human-related, environmental, and other social and economical factors.
TL;DR: The authors describe a self-serving asset built on an intelligent, self-aware agent platform that maximizes its service life by contacting, selecting, and procuring service providers autonomously.
Abstract: The authors describe a self-serving asset built on an intelligent, self-aware agent platform that maximizes its service life by contacting, selecting, and procuring service providers autonomously.
TL;DR: This work investigates the throughput maximizing data transmission strategy of an energy harvesting node which is able to harvest and store energy for communication and the impact of circuit power on the optimal transmission strategy and the maximal achievable throughput is studied.
Abstract: We investigate the throughput maximizing data transmission strategy of an energy harvesting node which is able to harvest and store energy for communication. Solar cell and rechargeable battery technologies have made such nodes feasible. In addition to the energy arrival process and the battery capacity limitation, the energy consumption of the circuits of the node also plays an important role in the way how the harvested energy should be utilized. To this end, we assume for the transmitting node an active mode for which a constant circuit power is incurred, and a sleep mode for which no energy is consumed. The criteria that an optimal transmission strategy should satisfy are discussed, and based on them, a construction procedure of the optimal transmission strategy is proposed. Numerical simulations are performed to verify the theoretical results, and the impact of circuit power on the optimal transmission strategy and the maximal achievable throughput is studied.
TL;DR: The Digital Asset Protection Association (DAPA) was launched to address the challenges specific to MATE attacks and software protection research in general, and the ultimate goal is to establish standards and baseline definitions for SP research.
Abstract: Man-at-the-end (MATE) attacks are an understudied branch of computer security These attacks involve an adversary gaining an advantage by violating software or hardware under their control, directly or via a remote connection On an individual scale, MATE attacks could violate the privacy and integrity of medical records and other sensitive personal data, and on a larger scale, they could cripple a national infrastructure (such as a power grid and the Internet itself) The goal of software protection (SP) research is to make software safe from such MATE attacks by preventing adversaries from tampering, reverse engineering, and illegally redistributing software In July 2011, the Digital Asset Protection Association (DAPA) was launched to address the challenges specific to MATE attacks and SP research in general As DAPA activities and efforts get underway, the ultimate goal is to establish standards and baseline definitions for SP research and to promote coordinated, open efforts among academia and industry
TL;DR: The approach for identifying subcortical targets during deep brain stimulation surgery is presented and pattern recognition approaches can help localize neural targets for therapeutic neurostimulation, such as deepbrain stimulation of the subthalamic nucleus in Parkinson's disease.
Abstract: This paper presents the approach for identifying subcortical targets during deep brain stimulation surgery.Pattern recognition approaches can help localize neural targets for therapeutic neurostimulation, such as deep brain stimulation of the subthalamic nucleus in Parkinson's disease. A variety of neurophysiological signals are routinely collected from patients with brain diseases in the hope that such signals contain meaningful patterns that reflect underlying pathological brain functions. However, little is understood about the underlying mechanisms of brain diseases because those data are often massive and noisy. Data processing tools might help extract meaningful, yet hidden, information from massive neuro physiological data for both clinical and scientific uses.
TL;DR: Video surveillance systems can capture pedestrian visual information to support their detection and behavior analysis, especially their interactions with vehicles, which can help identify impending traffic accidents.
Abstract: Over the last 30 years, video surveillance systems have been a key part of intelligent transportation systems (ITSs), which use various image sensors to capture visual information about vehicles and pedestrians to obtain real-time knowledge of traffic conditions. Specifically, they capture vehicles' visual appearances and support mining more information about them through ve hicle detection, localization, and classification; license plate recognition; vehicle-behavior analysis; and so forth. They also help generate overall vehicle statistics such as estimations of flow rate, average speed, and density. In addition, video surveillance systems can capture pedestrian visual information to support their detection and behavior analysis, especially their interactions with vehicles, which can help identify impending traffic accidents.
TL;DR: The paper states that integrating multiple types of intelligent, mulit-agent data analysis within a smart grid can pave the way for flexible, extensible, and robust solutions to power network management.
Abstract: The paper states that integrating multiple types of intelligent, mulit-agent data analysis within a smart grid can pave the way for flexible, extensible, and robust solutions to power network management.
TL;DR: The OSGi-based platform TaskShadow supports seamless task migration across smart environments using a task-to-service mapping algorithm to semantically search for suitable low-level services that achieve high-level tasks.
Abstract: The OSGi-based platform TaskShadow supports seamless task migration across smart environments using a task-to-service mapping algorithm to semantically search for suitable low-level services that achieve high-level tasks.
TL;DR: The automated, animated mediator AniMed* aims to increase the social welfare of people in bilateral negotiations, utilizing a generic strategy mechanism and the ability to propose partial solutions.
Abstract: The automated, animated mediator AniMed* aims to increase the social welfare of people in bilateral negotiations, utilizing a generic strategy mechanism and the ability to propose partial solutions.