Papers by Joseph Giampapa
Proceedings of the …, 2004
Abstract-A key prerequisite for higher-level fusion is the use of context to disambiguate and int... more Abstract-A key prerequisite for higher-level fusion is the use of context to disambiguate and interpret sensed data and guide data collection. For ground operations terrain information supplies an important context. The layout of terrain is a determining factor in arraying of ...
As a precursor to explorations on future network interoperability problem resolution methods and ... more As a precursor to explorations on future network interoperability problem resolution methods and tools, it is necessary to obtain an understanding of problems in the present day. The remote network access application area was chosen as a case study due to rich sources of information, frequent problems, and considerable detrimental impact on user efficiency. To this end, existing remote network access help desk data was acquired and analyzed. The data was used to characterize remote network access interoperability problems and identify key issues. For the data examined, the two largest problems specific to remote end users were obtaining modem phone numbers for their location and adequate user rights upon connection. Potential for better knowledge re-use and dissemination of solutions to common problems to the general population was also observed.
In the application domain of stock portfolio management, software agents that evaluate the risks ... more In the application domain of stock portfolio management, software agents that evaluate the risks associated with the individual companies of a portfolio should be able to read electronic news articles that are written to give investors an indication of the nancial outlook of a company. There is a positive correlation between news reports on a company's nancial outlook and the company's attractiveness as an investment. However, because of the volume of such reports, it is impossible for nancial analysts or investors to track and read each one. Therefore, it would be very helpful to have a system that automatically categorizes news reports that re ect positively or negatively on a company's nancial outlook. To accomplish this task, we treat the unsupervised reading and understanding of news articles as an automatic text classi cation problem. In this paper, we propose a text classi cation method that we call, \domain experts" and \self-con dent" sampling technique, and compare it with naive Bayes with expectation maximization (EM). We evaluate these learning techniques in terms of how well they improve with unlabeled data after being initially trained on a small number of human-labeled articles and how well they classify the latest nancial news articles. The signi cance of this work lies in the new classi cation method that we propose and in the sampling technique we used for improving classi cation accuracy.
Proceedings of the 38th Annual Hawaii International Conference on System Sciences, 2005
... Katia Sycara Robotics Institute Carnegie Mellon University 5000 Forbes Avenue Pittsburgh, PA ... more ... Katia Sycara Robotics Institute Carnegie Mellon University 5000 Forbes Avenue Pittsburgh, PA 15213 [email protected] Joseph Giampapa Robotics Institute Carnegie Mellon University 5000 Forbes Avenue Pittsburgh, PA 15213 [email protected] Abstract ...
Automated Multi-attribute Negotiation is an important and valuable mechanism in the Navy detailin... more Automated Multi-attribute Negotiation is an important and valuable mechanism in the Navy detailing system, in order to realize efficient, distributed and "Win-Win" matching. This report provides an extensive literature review of the existing research in Multiattribute Negotiations in the fields of Economics and Artificial Intelligence, discussing the motivation for multi-attribute negotiations, as well as some difficulties in implementation. Related to Multi-attribute Negotiations, approaches to preference elicitation and multi-criteria-decision-making are also reviewed. Based on the existing literature, we conclude that multi-attribute negotiation is an important as well as challenging research problem.
In the application domain of stock portfolio management, software agents that evaluate the risks ... more In the application domain of stock portfolio management, software agents that evaluate the risks associated with the individual companies of a portfolio should be able to read electronic news articles that are written to give investors an indication of the financial outlook of a company. There is a positive correlation between news reports on a company's financial outlook and the company's attractiveness as an investment. However, because of the volume of such reports, it is impossible for financial analysts or investors to track and read each one. Therefore, it would be very helpful to have a system that automatically classifies news reports that reflect positively or negatively on a company's financial outlook. To accomplish this task, we treat the analysis of news articles as a text classification problem. We developed a text classification algorithm that classifies financial news article by using a combination of a reduced but highly informative word feature sets and a variant of weighted majority algorithm. By clustering words represented in latent semantic vector space by LSA into groups with similar concepts, we are able to find semantically coherent word groups. A learning method with unlabeled data "Self-Confident" sampling was proposed to handle the problem of expensive data labeling. Vote entropy is the criterion that information-theoretically assigns a label to an unlabeled document. In comparison with naive Bayes classification boosted by Expectation Maximization (EM), the proposed method showed a better performance in terms of accuracy. Two criteria are used to evaluate methods: how well they improve their performances with unlabeled data after being initially trained on a small number of human-labeled articles and how well they classify the latest financial news articles which are mostly not seen during the training. The contribution of this work lies in the new classification method that we propose and in the sampling technique we used for improving classification accuracy.
... by Wei Yang , Katia Sycara , Joseph Giampapa. Add To MetaCart. ...
... by Cuihong Li , Katia Sycara , Joseph Giampapa. Add ... Add a tag: No tags have been applied ... more ... by Cuihong Li , Katia Sycara , Joseph Giampapa. Add ... Add a tag: No tags have been applied to this document. BibTeX | Add To MetaCart. @MISC{Li03navydetailing, author = {Cuihong Li and Katia Sycara and Joseph Giampapa}, title = {Navy Detailing Process,}, year = {2003} }. ...
The U.S. Navy detailing process is the matching process for assigning Sailors to available billet... more The U.S. Navy detailing process is the matching process for assigning Sailors to available billets. This paper studies a new two-sided matching process for the detailing process to reduce the number of detailers, simplify the assignment process, and increase the satisfaction of Sailors and Commands. We focus on two-sided matching with market complications such as married couples looking for related
Recently the number of autonomous agents and multiagent systems MAS that have been developed by d... more Recently the number of autonomous agents and multiagent systems MAS that have been developed by di erent developers has increased. Despite e orts for the creation of standards eg. in communication languages, registration protocols etc., it is clear that at least in the near term heterogeneous agents and MASs will be prevalent. Therefore, mechanisms that allow agents and or MASs to interoperate and transact are needed. In this paper we report on a case study and lessons learned of an interoperator agent we developed. We discuss requirements for interoperation mechanisms, resulting challenges and our design decisions and implementation of the RETSINA-OAA InterOperator 1 .
Lecture Notes in Computer Science, 2014
Recently the number of autonomous agents and multiagent systems (MAS) that have been developed by... more Recently the number of autonomous agents and multiagent systems (MAS) that have been developed by different developers has increased. Despite efforts for the creation of standards (eg. in communication languages, registration protocols etc.), it is clear that at least in the near term heterogeneous agents and MASs will be prevalent. Therefore, mechanisms that allow agents and/or MASs to interoperate and transact are needed. In this paper we report on a case study and lessons learned of an interoperator agent we developed. We discuss requirements for interoperation mechanisms, resulting challenges and our design decisions and implementation of the RETSINA-OAA InterOperator
Lecture Notes in Computer Science, 2013
Lecture Notes in Computer Science, 2013
Robots are increasingly used to perform a wide variety of tasks, especially those involving dange... more Robots are increasingly used to perform a wide variety of tasks, especially those involving dangerous or inaccessible locations. As the complexity of such tasks grow, robots are being deployed in teams, with complex coordination schemes aimed at maximizing the chance of mission success. Such teams operate under inherently uncertain conditions-the robots themselves fail, and have to continuously adapt to changing environmental conditions. A key challenge facing robotic mission designers is therefore to construct a mission-i.e., specify number and type of robots, number and size of teams, coordination and planning mechanisms etc.-so as to maximize some overall utility, such as probability of mission success. In this paper, we advocate, formalize, and empirically justify an approach to compute quantitative utility of robotic missions using probabilistic model checking. We show how to express a robotic demining mission as a restricted type of discrete time Markov chain (called αPA), and its utility as either a linear temporal logic formula or a reward. We prove a set of compositionality theorems that enable us to compute the utility a system composed of several αPAs by combining the utilities of each αPA in isolation. This ameliorates the statespace explosion problem, even when the system being verified is composed of a larger number of robots. We validate our approach empirically, using the probabilistic model checker prism.
The creation of joint plans within teams is a complex task, especially if these teams are formed ... more The creation of joint plans within teams is a complex task, especially if these teams are formed in an ad-hoc fashion with limited co-training. Team members may have to plan their actions in accordance with a set of regulations or mission policies and by observing planning constraints. For ad-hoc teams operating under time-stressed conditions, this is a difficult task. In this paper, we describe how to construct agents that can support teams in their collaborative planning effort. We show how agents can be integrated into the planning and communication activities of human planners. Agents monitor human planners, reason about their actions and advise them on possible violations of mission policies and planning constraints.
The U.S. Navy detailing process is the matching process for assigning Sailors to available billet... more The U.S. Navy detailing process is the matching process for assigning Sailors to available billets. This paper studies a new two-sided matching process for the detailing process to reduce the number of detailers, simplify the assignment process, and increase the satisfaction of Sailors and Commands. We focus on two-sided matching with market complications such as married couples looking for related positions. The existence of stable matchings is established by assuming all couples have responsive preferences, which means the unilateral improvement of one partner's job is considered beneficial for the couple as well. Based on its unique features and special requirements, we design a two-sided matching algorithm for the detailing process with the consideration of market complications including married couples, priority billets that must be filled, and high fill rate for Sailors. We believe that this algorithm deals with these market complications in an appropriate manner.
IEEE Transactions on Smart Grid, 2000
This paper introduces new analytical techniques for performing vulnerability analysis of state es... more This paper introduces new analytical techniques for performing vulnerability analysis of state estimation when it is subject to a hidden false data injection cyber-attack on a power grid's SCADA system. Specifically, we consider ac state estimation and describe how the physical properties of the system can be used as an advantage in protecting the power system from such an attack. We present an algorithm based on graph theory which allows determining how many and which measurement signals an attacker will attack in order to minimize his efforts in keeping the attack hidden from bad data detection. This provides guidance on which measurements are vulnerable and need increased protection. Hence, this paper provides insights into the vulnerabilities but also the inherent strengths provided by ac state estimation and network topology features such as buses without power injections.
Coalition forces are engaged in distributed collaborative decision making in time-pressured, high... more Coalition forces are engaged in distributed collaborative decision making in time-pressured, high-stakes situations. Providing automated decision support for such environments is a very challenging problem, due to shortening decision cycles, the changing nature of threats, opponent tactics, and environmental unpredictability. Intelligent agents have the promise to provide timely assistance in various areas of decentralized, collaborative decision making, such as information gathering, information dissemination, monitoring of team progress and alerting the team to various unexpected events. In order to fulfil the promise of agent technology in providing effective team assistance, better understanding of robust human-agent teamwork is crucial. The goal of our research project is to develop a theoretically grounded and empirically tested framework to allow for effective agent support for human teams that are engaged in adaptive teamwork in dynamic environments. In order to (a) establish an experimental baseline of the performance of human-only teams and (b) understand where agents can provide the best utility in supporting human teamwork, we designed a scenario and experimentally evaluated team work where human teams performed a time-stressed, collaborative search task in a multi-player gaming environment. The collaborative search task recreates some of the challenges faced by human teams during search and rescue operations in the real world. In our experiments, we analyze (1) verbal communication between team members and (2) team coverage patterns. By ascertaining the information processing and coordination requirements of this team task, we can identify ``insertion points'' for agent assistance to human teams. The search patterns demonstrated by the experimental subjects exhibited similar problems to the behavior of actual search and rescue teams: (1) the creation of accidental holes in the search pattern due to poor execution of the search plan, and (2) poor priority assignments in the search plan due to false clues and hunches. We have identified that this is a promising area for agent assistance. By having agents monitor and track individual team members' coverage, gaps in the team coverage are exposed earlier in the search process allowing repairs to be made in a more timely fashion. Our model predicts that aiding the state of coordination between team members will result in task performance improvement.
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Papers by Joseph Giampapa