This paper focuses on effectiveness of methods for improving patient quality (e.g. improving treatment adherence, reducing adverse events) outcomes and targeted interventions based on psychosocial and clinical risk factors embedded structured and unstructured elements in medical records. Current methods on outcomes analysis such as adherence to treatment regimen largely rely on survey instruments, and provide lagging indicators that inhibits timely intervention and care services. In this paper we present a novel early-warning method that can predict patients at risk of non-adherence based on clinical rules, natural language processing techniques and predictive algorithms applied to risk factor information embedded in electronic medical records. We conducted studies on the effectiveness of our risk estimation methods across 2.5 million patient-visit records from a community cancer clinic that spans a 14 year time-horizon. We identified 2 distinct patient groups, between 26 and 38 (mean risk score, r=0.77, s=0.22), and 75 and 90 (r=0.81, s=0.19) years of age respectively, who exhibited a strong likelihood of non-adherence to treatment regimen. We obtained a reasonably high C-statistic (> 0.77) on predicting outcomes based on the risk factors. The dominant risk-factors, not surprisingly, included psychosocial (e.g. depression and lack of support), medical (e.g. side-effects) and financial (e.g. co-pay). We finally discuss the effectiveness of the methods for targeted and improved health care services.

We experimentally investigate a combinatorial double-sided auction mechanism for allocation of bandwidth between buyers and sellers. The purpose of the experiment is to investigate the efficiency of the mechanism proposed in Jain & Varaiya (2004a) as well as the bidder behavior. We have implemented the mechanism in a combinatorial auction experimental platform which was used for this investigation. We performed experiments utilizing a simplified version of the theory using two different network structures, one with full valuations over every link and another with valuations only on specific combinations with restricted supply. Experimental results show that the mechanism gets close but not achieve competitive equilibrium. The market conditions also affect the efficiency of the mechanism. In cases where the supply was restricted and the demand was on packages rather than single links, has disciplined sellers to overbid less and the buyers to underbid less. Experience from both buyers and sellers let to more efficient results. Observed prices were closer to competitive equilibrium prices under the constrained market conditions.

We conduct a human experimental and computational simulation investigation of the efficiency properties of a combinatorial double-sided sealed-bid uniform price auction mechanism for allocation of bandwidth over combinations of links to form routes. Two different market structures are used: the benchmark case with valuations over every route combination and the alternative case with buyer valuations only on specific combinations and restricted supply of links. Experimental results show that the mechanism achieves an average of 78% and 87% efficiency in the benchmark and alternative cases respectively. Implementing a naive-bidding strategy in an iterative version of the benchmark case improves efficiency, with bigger improvements as the number of participants increases.

NASA Ames’ Mobile Agents Architecture is a distributed agent-based architecture, which integrates diverse mobile entities in a wide-area wireless system for lunar and planetary surface operations. Software agents, implemented in the Brahms multiagent language, run in Brahms virtual machines onboard laptops for space suits, robots, and surface habitats. “Personal agents” support the habitat crew and surface astronauts, as well as the their robotic assistant. People communicate with their personal agents via a speech dialogue system and via a meeting-capture hyperlink database tool.

Future human planetary exploration creates challenges both for technology and mission management. Ubiquitous computing principles and applied artificial intelligence are promising approaches in making planetary surface missions safer and more effective. Architectures which integrate both approaches and facilitate the interaction and collaboration between astronauts, robots, systems, and remote science teams are necessary to achieve these goals. The Mobile Agents project uses a real-time distributed multi-agent architecture and system to provide model-based real-time distributed support for human-robotic collaboration, science data collection, mission-plan tracking, and health monitoring. The Brahms agent-oriented modeling environment provides a layer of abstraction for enabling a diversity of software, hardware, and humans to be integrated into data management and workflow. Brahms agents facilitate the communication between different mission participants and interact through voice interfaces with astronauts, remote science teams, and mission control. This paper presents the astronaut-robotic planetary exploration environment as an example of ubiquitous computing. It also discusses an area largely unexplored in the ubiquitous/pervasive literature, namely human-robotic interaction through a localized or tele-operated ubiquitous computing system. The Mobile Agents Architecture is presented and the agent-layer aspects which related to human-robotic pervasive systems are further discussed. We conclude with remarks about evaluation of the architecture through field testing.

Over the last few years there have been a lot of discussions about sharing of digital content over the Internet as well as University networks. In parallel, temporary local networks have been established on a regular basis to facilitate multi-player gaming. The similarities between these networks and University networks, both in technical terms and user profiles, provides the motivation to further explore this new phenomena of LAN-parties, currently unknown to most researchers and practitioners, to better understand if they have any impact on content distribution. Using empirical data coming from a survey conducted at various LAN-parties, we find that: gaming is not a dominant motivation to attend LAN-parties; the average amount of files provided and downloaded at these events is much higher than on P2P networks; free-riding is present for all kinds of content; and LAN-parties tend to favor sharing of larger files such as movies compared to P2P networks.

A model-based, distributed architecture integrates diverse components in a system designed for lunar and planetary surface operations: spacesuit biosensors, cameras, GPS, and a robotic assistant. The system transmits data and assists communication between the extra-vehicular activity (EVA) astronauts, the crew in a local habitat, and a remote mission support team. Software processes ("agents"), implemented in a system called Brahms, run on multiple, mobile platforms, including the spacesuit backpacks, all-terrain vehicles, and robot. These "mobile agents" interpret and transform available data to help people and robotic systems coordinate their actions to make operations more safe and efficient. Different types of agents relate platforms to each other ("proxy agents"), devices to software ("comm agents"), and people to the system ("personal agents"). A state-of-the-art spoken dialogue interface enables people to communicate with their personal agents, supporting a speech-driven navigation and scheduling tool, field observation record, and rover command system. An important aspect of the engineering methodology involves first simulating the entire hardware and software system in Brahms, and then configuring the agents into a runtime system. Design of mobile agent functionality has been based on ethnographic observation of scientists working in Mars analog settings in the High Canadian Arctic on Devon Island and the southeast Utah desert. The Mobile Agents system is developed iteratively in the context of use, with people doing authentic work. This paper provides a brief introduction to the architecture and emphasizes the method of empirical requirements analysis, through which observation, modeling, design, and testing are integrated in simulated EVA operations.

The Mobile Agents model-based, distributed architecture, which integrates diverse components in a system for lunar and planetary surface operations, was extensively tested in a two-week field "technology retreat" at the Mars Society s Desert Research Station (MDRS) during April 2003. More than twenty scientists and engineers from three NASA centers and two universities refined and tested the system through a series of incremental scenarios. Agent software, implemented in runtime Brahms, processed GPS, health data, and voice commands-monitoring, controlling and logging science data throughout simulated EVAs with two geologists. Predefined EVA plans, modified on the fly by voice command, enabled the Mobile Agents system to provide navigation and timing advice. Communications were maintained over five wireless nodes distributed over hills and into canyons for 5 km; data, including photographs and status was transmitted automatically to the desktop at mission control in Houston. This paper describes the system configurations, communication protocols, scenarios, and test results.

We have developed a model-based, distributed architecture that integrates diverse components in a system designed for lunar and planetary surface operations: an astronaut’s space suit, cameras, all-terrain vehicles, robotic assistant, crew in a local habitat, and mission support team. Software processes (“agents”) implemented in the Brahms language, run on multiple, mobile platforms. These “mobile agents” interpret and transform available data to help people and robotic systems coordinate their actions to make operations more safe and efficient. The Brahms-based mobile agent architecture (MAA) uses a novel combination of agent types so the software agents may understand and facilitate communications between people and between system components. A state-of-the-art spoken dialogue interface is integrated with Brahms models, supporting a speech-driven field observation record and rover command system. An important aspect of the methodology involves first simulating the entire system in Brahms, then configuring the agents into a runtime system Thus, Brahms provides a language, engine, and system builder’s toolkit for specifying and implementing multiagent systems.

We have developed a model-based, distributed architecture that integrates diverse components in a system designed for lunar and planetary surface operations: an astronaut's space suit, cameras, rover/All-Terrain Vehicle (ATV), robotic assistant, other personnel in a local habitat, and a remote mission support team (with time delay). Software processes, called "agents," implemented in the Brahms language (Clancey, et al. 1998; Sierhuis 2001), run on multiple, mobile platforms. These "mobile agents" interpret and transform available data to help people and robotic systems coordinate their actions to make operations more safe and efficient. The Brahms-based mobile agent architecture (MAA) uses a novel combination of agent types so the software agents may understand and facilitate communications between people and between system components. A state-of-the-art spoken dialogue interface is integrated with Brahms models, supporting a speech-driven field observation record and rover command system (e.g., "return here later and bring this back to the habitat"). This combination of agents, rover, and model-based spoken dialogue interface constitutes a "personal assistant." An important aspect of the methodology involves first simulating the entire system in Brahms, then configuring the agents into a run-time system

We have developed a model-based, distributed architecture that integrates diverse components in a system designed for lunar and planetary surface operations: an astronaut’s space suit, cameras, rover/All-Terrain Vehicle (ATV), robotic assistant, other personnel in a local habitat, and a remote mission support team (with time delay). Software processes, called “agents,” implemented in the Brahms language (Clancey, et al. 1998; Sierhuis 2001), run on multiple, mobile platforms. These “mobile agents” interpret and transform available data to help people and robotic systems coordinate their actions to make operations more safe and efficient. The Brahms-based mobile agent architecture (MAA) uses a novel combination of agent types so the software agents may understand and facilitate communications between people and between system components. A state-of-the-art spoken dialogue interface is integrated with Brahms models, supporting a speech-driven field observation record and rover command system (e.g., "return here later and bring this back to the habitat"). This combination of agents, rover, and model-based spoken dialogue interface constitutes a “personal assistant.” An important aspect of the methodology involves first simulating the entire system in Brahms, then configuring the agents into a run-time system