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An ambient intelligence approach for learning in smart robotic environments
Università di Pisa, Pisa, Italy.
Örebro University, Örebro, Sweden.
Heriot-Watt University, Edinburgh, UK.
Università di Pisa, Pisa, Italy.
Vise andre og tillknytning
2019 (engelsk)Inngår i: Computational intelligence, ISSN 0824-7935, E-ISSN 1467-8640Artikkel i tidsskrift (Fagfellevurdert) Epub ahead of print
Abstract [en]

Smart robotic environments combine traditional (ambient) sensing devices and mobile robots. This combination extends the type of applications that can be considered, reduces their complexity, and enhances the individual values of the devices involved by enabling new services that cannot be performed by a single device. To reduce the amount of preparation and preprogramming required for their deployment in real-world applications, it is important to make these systems self-adapting. The solution presented in this paper is based upon a type of compositional adaptation where (possibly multiple) plans of actions are created through planning and involve the activation of pre-existing capabilities. All the devices in the smart environment participate in a pervasive learning infrastructure, which is exploited to recognize which plans of actions are most suited to the current situation. The system is evaluated in experiments run in a real domestic environment, showing its ability to proactively and smoothly adapt to subtle changes in the environment and in the habits and preferences of their user(s), in presence of appropriately defined performance measuring functions.

sted, utgiver, år, opplag, sider
Wiley-Blackwell, 2019.
Emneord [en]
Adaptive planning, ambient intelligence, recurrent neural networks, robotic ecology, self-adaptive system, smart environment
HSV kategori
Identifikatorer
URN: urn:nbn:se:oru:diva-75959DOI: 10.1111/coin.12233ISI: 000481324700001OAI: oai:DiVA.org:oru-75959DiVA, id: diva2:1346938
Merknad

Funding Agency:

European Commission  FP7-ICT-269914

Tilgjengelig fra: 2019-08-29 Laget: 2019-08-29 Sist oppdatert: 2019-10-17bibliografisk kontrollert

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