Novelty Detection as an Intrinsic Motivation for Cumulative Learning Robots

Author(s):  
Ulrich Nehmzow ◽  
Yiannis Gatsoulis ◽  
Emmett Kerr ◽  
Joan Condell ◽  
Nazmul Siddique ◽  
...  
2017 ◽  
Vol 8 (1) ◽  
pp. 58-69 ◽  
Author(s):  
Nazmul Siddique ◽  
Paresh Dhakan ◽  
Inaki Rano ◽  
Kathryn Merrick

Abstract This paper presents a review on the tri-partite relationship between novelty, intrinsic motivation and reinforcement learning. The paper first presents a literature survey on novelty and the different computational models of novelty detection, with a specific focus on the features of stimuli that trigger a Hedonic value for generating a novelty signal. It then presents an overview of intrinsic motivation and investigations into different models with the aim of exploring deeper co-relationships between specific features of a novelty signal and its effect on intrinsic motivation in producing a reward function. Finally, it presents survey results on reinforcement learning, different models and their functional relationship with intrinsic motivation.


2004 ◽  
Vol 49 (5) ◽  
pp. 532-534 ◽  
Author(s):  
Dale H. Schunk
Keyword(s):  

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