Andrzej Uszok

Bio: Andrzej Uszok is an academic researcher from University of West Florida. The author has contributed to research in topics: KAOS & Multi-agent system. The author has an hindex of 13, co-authored 23 publications receiving 898 citations. Previous affiliations of Andrzej Uszok include Florida Institute for Human and Machine Cognition.

Semantic web languages for policy representation and reasoning: a comparison of KAoS, Rei, and Ponder

Abstract: Policies are being increasingly used for automated system management and controlling the behavior of complex systems. The use of policies allows administrators to modify system behavior without changing source code or requiring the consent or cooperation of the components being governed. Early approaches to policy representation have been restrictive in many ways. However semantically-rich policy representations can reduce human error, simplify policy analysis, reduce policy conflicts, and facilitate interoperability. In this paper, we compare three approaches to policy representation, reasoning, and enforcement. We highlight similarities and differences between Ponder, KAoS, and Rei, and sketch out some general criteria and properties for more adequate approaches to policy semantics in the future.

Dimensions of adjustable autonomy and mixed-initiative interaction

Abstract: Several research groups have grappled with the problem of characterizing and developing practical approaches for implementing adjustable autonomy and mixed-initiative interaction in deployed systems. However, each group takes a little different approach and uses variations of the same terminology in a somewhat different fashion. In this chapter, we will describe some common dimensions in an effort to better understand these important but ill-characterized topics. We are developing a formalism and implementation of these concepts as part of the KAoS framework in the context of our research on policy-governed autonomous systems.

Adjustable Autonomy and Human-Agent Teamwork in Practice: An Interim Report on Space Applications

Abstract: We give a preliminary perspective on the basic principles and pitfalls of adjustable autonomy and human-centered teamwork. We then summarize the interim results of our study on the problem of work practice modeling and human-agent collaboration in space applications, the development of a broad model of human-agent teamwork grounded in practice, and the integration of the Brahms, KAoS, and NOMADS agent frameworks We hope our work will benefit those who plan and participate in work activities in a wide variety of space applications, as well as those who are interested in design and execution tools for teams of robots that can function as effective assistants to humans.

Dimensions of adjustable autonomy and mixed-initiative-interaction

Abstract: Several research groups have grappled with the problem of characterizing and developing practical approaches for implementing adjustable autonomy and mixed-initiative interaction in deployed systems. However, each group takes a little different approach and uses variations of the same terminology in a somewhat different fashion. In this chapter, we will describe some common dimensions in an effort to better understand these important but ill-characterized topics. We are developing a formalism and implementation of these concepts as part of the KAoS framework in the context of our research on policy-governed autonomous systems.

DAML-based policy enforcement for semantic data transformation and filtering in multi-agent systems

Abstract: This paper describes an approach to runtime policy-based control over information exchange that allows a far more fine-grained control of these dynamically discovered agent interactions. The DARPA Agent Markup Language (DAML) is used to represent policies that may either filter messages based on their semantic content or transform the messages to make them suitable to be released. Policy definition, management, and enforcement are realized as part of the KAoS architecture. The solutions presented have been tested in the Coalition Agents Experiment (CoAX) - an experiment involving coalition military operations.

打磨Using Language,倡导新理念

Abstract: 人教版高中英语新课程教材中,语言运用（Using Language）是每个单元必不可少的部分,提供了围绕单元中心话题的听、说、读、写的综合性练习,是单元中心话题的延续和升华.如何设计Using Language部分的教学,使自己的教学模式既不落俗套,又能真正体现新课程标准所倡导的教学理念,正是广大一线英语教师一直努力探索的问题.

Situations and Attitudes.

Abstract: In this provocative book, Barwise and Perry tackle the slippery subject of \"meaning, \" a subject that has long vexed linguists, language philosophers, and logicians.

Human-Robot Interaction: A Survey

Abstract: Human-Robot Interaction (HRI) has recently received considerable attention in the academic community, in labs, in technology companies, and through the media. Because of this attention, it is desirable to present a survey of HRI to serve as a tutorial to people outside the field and to promote discussion of a unified vision of HRI within the field. The goal of this review is to present a unified treatment of HRI-related problems, to identify key themes, and discuss challenge problems that are likely to shape the field in the near future. Although the review follows a survey structure, the goal of presenting a coherent "story" of HRI means that there are necessarily some well-written, intriguing, and influential papers that are not referenced. Instead of trying to survey every paper, we describe the HRI story from multiple perspectives with an eye toward identifying themes that cross applications. The survey attempts to include papers that represent a fair cross section of the universities, government efforts, industry labs, and countries that contribute to HRI, and a cross section of the disciplines that contribute to the field, such as human, factors, robotics, cognitive psychology, and design.

Applying KAoS services to ensure policy compliance for semantic web services workflow composition and enactment

Abstract: In this paper we describe our experience in applying KAoS services to ensure policy compliance for Semantic Web Services workflow composition and enactment. We are developing these capabilities within the context of two applications: Coalition Search and Rescue (CoSAR-TS) and Semantic Firewall (SFW). We describe how this work has uncovered requirements for increasing the expressivity of policy beyond what can be done with description logic (e.g., role-value-maps), and how we are extending our representation and reasoning mechanisms in a carefully controlled manner to that end. Since KAoS employs OWL for policy representation, it fits naturally with the use of OWL-S workflow descriptions generated by the AIAI I-X planning system in the CoSAR-TS application. The advanced reasoning mechanisms of KAoS are based on the JTP inference engine and enable the analysis of classes and instances of processes from a policy perspective. As the result of analysis, KAoS concludes whether a particular workflow step is allowed by policy and whether the performance of this step would incur additional policy-generated obligations. Issues in the representation of processes within OWL-S are described. Besides what is done during workflow composition, aspects of policy compliance can be checked at runtime when a workflow is enacted. We illustrate these capabilities through two application examples. Finally, we outline plans for future work.