5,922 research outputs found

    A distributed agent architecture for real-time knowledge-based systems: Real-time expert systems project, phase 1

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    We propose a distributed agent architecture (DAA) that can support a variety of paradigms based on both traditional real-time computing and artificial intelligence. DAA consists of distributed agents that are classified into two categories: reactive and cognitive. Reactive agents can be implemented directly in Ada to meet hard real-time requirements and be deployed on on-board embedded processors. A traditional real-time computing methodology under consideration is the rate monotonic theory that can guarantee schedulability based on analytical methods. AI techniques under consideration for reactive agents are approximate or anytime reasoning that can be implemented using Bayesian belief networks as in Guardian. Cognitive agents are traditional expert systems that can be implemented in ART-Ada to meet soft real-time requirements. During the initial design of cognitive agents, it is critical to consider the migration path that would allow initial deployment on ground-based workstations with eventual deployment on on-board processors. ART-Ada technology enables this migration while Lisp-based technologies make it difficult if not impossible. In addition to reactive and cognitive agents, a meta-level agent would be needed to coordinate multiple agents and to provide meta-level control

    Agents for educational games and simulations

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    This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications

    Developing An Object-oriented Approach For Operations Simulation In Speedes

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    Using simulation techniques, performance of any proposed system can be tested for different scenarios with a generated model. However, it is difficult to rapidly create simulation models that will accurately represent the complexity of the system. In recent years, Object-Oriented Discrete-Event Simulation has emerged as the potential technology to implement rapid simulation schemes. A number of software based on programming languages like C++ and Java are available for carrying out Object Oriented Discrete-Event Simulation. These software packages establish a general framework for simulation in computer programs, but need to be further customized for desired end-use applications. In this thesis, a generic simulation library is created for the distributed Synchronous Parallel Environment for Emulation and Discrete-Event Simulation (SPEEDES). This library offers classes to model the functionality of servers, processes, resources, transporters, and decisions. The library is expected to produce efficient simulation models in less time and with a lesser amount of coding. The class hierarchy is modeled using the Unified Modeling Language (UML). To test the library, the existing SPEEDES Space Shuttle Model is enhanced and recreated. This enhanced model is successfully validated against the original Arena model

    Factors shaping the evolution of electronic documentation systems

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    The main goal is to prepare the space station technical and managerial structure for likely changes in the creation, capture, transfer, and utilization of knowledge. By anticipating advances, the design of Space Station Project (SSP) information systems can be tailored to facilitate a progression of increasingly sophisticated strategies as the space station evolves. Future generations of advanced information systems will use increases in power to deliver environmentally meaningful, contextually targeted, interconnected data (knowledge). The concept of a Knowledge Base Management System is emerging when the problem is focused on how information systems can perform such a conversion of raw data. Such a system would include traditional management functions for large space databases. Added artificial intelligence features might encompass co-existing knowledge representation schemes; effective control structures for deductive, plausible, and inductive reasoning; means for knowledge acquisition, refinement, and validation; explanation facilities; and dynamic human intervention. The major areas covered include: alternative knowledge representation approaches; advanced user interface capabilities; computer-supported cooperative work; the evolution of information system hardware; standardization, compatibility, and connectivity; and organizational impacts of information intensive environments

    Virtual Reality Games for Motor Rehabilitation

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    This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion

    Human Factors in Agile Software Development

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    Through our four years experiments on students' Scrum based agile software development (ASD) process, we have gained deep understanding into the human factors of agile methodology. We designed an agile project management tool - the HASE collaboration development platform to support more than 400 students self-organized into 80 teams to practice ASD. In this thesis, Based on our experiments, simulations and analysis, we contributed a series of solutions and insights in this researches, including 1) a Goal Net based method to enhance goal and requirement management for ASD process, 2) a novel Simple Multi-Agent Real-Time (SMART) approach to enhance intelligent task allocation for ASD process, 3) a Fuzzy Cognitive Maps (FCMs) based method to enhance emotion and morale management for ASD process, 4) the first large scale in-depth empirical insights on human factors in ASD process which have not yet been well studied by existing research, and 5) the first to identify ASD process as a human-computation system that exploit human efforts to perform tasks that computers are not good at solving. On the other hand, computers can assist human decision making in the ASD process.Comment: Book Draf

    Working notes of the KI \u2796 Workshop on Agent Oriented Programming and Distributed Systems

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    Agent-oriented techniques are likely to be the next significant breakthrough in software development process. They provide a uniform approach throughout the analysis, design and implementation phases in the development life cycle. Agent-oriented techniques are a natural extension to object-oriented techniques, but while there is a whole pIethora of analysis and design methods in the object-oriented paradigm, very little work has been reported on design and analysis methods in the agent-oriented community. After surveying and examining a number of well-known object-oriented design and analysis methods, we argue that none of these methods, provide the adequate model for the design and analysis of multi-agent systems. Therefore, we propose a new agent-specific methodology that is based on and builds upon object-oriented methods. We identify three major models that need to be build during the development of multi-agent applications and describe the process of building these models

    The 7th Conference of PhD Students in Computer Science

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