Learning Information Acquisition for Multitasking Scenarios in Dynamic Environments

Abstract

Real world environments are so dynamic and unpredictable that a goal-oriented autonomous system performing a set of tasks repeatedly never experiences the same situation even though the task routines are the same. Hence, manually designed solutions to execute such tasks are likely to fail due to such variations. Developmental approaches seek to solve this… (More)
DOI: 10.1109/TAMD.2012.2226241

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Cite this paper

@article{Karaoguz2013LearningIA, title={Learning Information Acquisition for Multitasking Scenarios in Dynamic Environments}, author={Cem Karaoguz and Tobias Rodemann and Britta Wrede and Christian Goerick}, journal={IEEE Transactions on Autonomous Mental Development}, year={2013}, volume={5}, pages={46-61} }