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» Learning the required number of agents for complex tasks
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AAAI
2008
13 years 10 months ago
Reducing Particle Filtering Complexity for 3D Motion Capture using Dynamic Bayesian Networks
Particle filtering algorithms can be used for the monitoring of dynamic systems with continuous state variables and without any constraints on the form of the probability distribu...
Cédric Rose, Jamal Saboune, François...
CIA
2006
Springer
13 years 11 months ago
Iterative Query-Based Approach to Efficient Task Decomposition and Resource Allocation
Intelligent coordination in complex multi-agent environments requires sophisticated mechanisms for suboptimal task decomposition and efficient resource allocation provided by the t...
Michal Pechoucek, Ondrej Lerch, Jirí B&iacu...
IUI
2009
ACM
14 years 4 months ago
Learning to generalize for complex selection tasks
Selection tasks are common in modern computer interfaces: we are often required to select a set of files, emails, data entries, and the like. File and data browsers have sorting a...
Alan Ritter, Sumit Basu
WER
2004
Springer
14 years 29 days ago
Enhancing Requirements to derive Multi-Agent Architectures
Software systems of today are characterized by the increasing size, complexity, distribution and heterogeneity. Understanding and supporting the interaction between software requir...
Lúcia R. D. Bastos, Jaelson Brelaz de Castr...
CSL
1998
Springer
13 years 7 months ago
Evaluating spoken dialogue agents with PARADISE: Two case studies
This paper presents PARADISE PARAdigm for DIalogue System Evaluation, a general framework for evaluating and comparing the performance of spoken dialogue agents. The framework d...
Marilyn A. Walker, Diane J. Litman, Candace A. Kam...