Artificial intelligence publications
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Integrating Planning and Scheduling through Adaptation of Resource Intensity Estimates
We describe an incremental and adaptive approach to integrating hierarchical task network planning and constraint-based scheduling.
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Integrating Planning and Scheduling through Intensity Adaptation
We describe an incremental and adaptive approach to integrating hierarchical task network planning and constraint-based scheduling.
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Representational Issues for Real-world Planning Systems
This workshop brought together researchers and practitioners interested in representational issues for this broader model of planning systems.
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CODA: Coordinating Human Planners
The CODA system provides targeted information dissemination among distributed human planners as a way of improving coordination.
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Behavioral Contracts and Behavioral Subtyping
In this paper, we show how to enforce contracts if components are manufactured from class and interface hierarchies.
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Nutrient-related Analysis of Pathway/Genome Databases
We present an algorithm that solves two related problems in the analysis of metabolic networks stored within a pathway/genome database.
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Directing Agent Communities: An Initial Framework
This paper presents a framework for directability of a community of agents by a human supervisor that focuses on three dimensions: adjustable agent autonomy, strategy preference, and community-level constraints.
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The .geo-web: A Scalable Index for the Digital Earth
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Structured Argumentation for Analysis
We are developing a new methodology that retains the ease-of-use, familiarity, and (some of) the free-form nature of informal methods, while benefiting from the rigor, structure, and potential for automation…
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Reusing Prior Knowledge: Problems and Solutions
In this paper, we focus on the process of reuse and report a case study on constructing a KB by reusing existing knowledge. The reuse process involved the following steps:…
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Measuring the Self-Consistency of Stereo Algorithms
A new approach to characterizing the performance of point-correspondence algorithms is presented. Instead of relying on any "ground truth", it uses the self-consistency of the outputs of an algorithm independently…
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Multiple-Target Tracking and Data Fusion via Probabilistic Mapping
A new approach is taken to address the various aspects of the multi-sensor, multi-target tracking (MTT) problem in dense and noisy environments. Instead of fixing the trackers on the potential…