Title
Recipe tuning by reinforcement learning in the SandS ecosystem
Abstract
The Social and Smart (SandS) project ecosystem is compounded of household appliance users sharing recipes for the used of appliances, an intermediate control layer, and an intelligent social layer which aims to optimize the appliance recipes maximizing user satisfaction. We consider two aspects of the social intelligence, the innovation producing new recipes for unkown user tasks, and the adaptation to personalize the recipe to an individual user on the basis of his/her specific feedback. The second aspect is proposed to be dealt with by Reinforcement Learning approach, thus user feedback becomes the system reward. In this paper we discuss such an architecture based on the actor-critic approach, providing some experimental results on synthetic datasets that demonstrate the feasibility of the approach, previous to real life implementations.
Year
DOI
Venue
2014
10.1109/CASoN.2014.6920422
Computational Aspects of Social Networks
Keywords
Field
DocType
domestic appliances,learning (artificial intelligence),social sciences computing,user interfaces,SandS ecosystem,actor-critic approach,household appliance,intelligent social layer,recipe tuning,reinforcement learning,social and smart project ecosystem,social intelligence,user satisfaction,Reinforcement Learning,Social computing,Social networks,subconscious social intelligence
Control layer,Data mining,Architecture,Social network,Computer science,Implementation,Recipe,Artificial intelligence,Social intelligence,Social computing,Machine learning,Reinforcement learning
Conference
ISSN
Citations 
PageRank 
2155-7047
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Borja Fernández-Gauna1315.82
Manuel Graña21367156.11
Fernandez-Gauna, B.300.34