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Neural Computing and Applications
Erschienen in: Neural Computing and Applications 4/2017

19.11.2015 | Original Article

Application of emotion affected associative memory based on mood congruency effects for a humanoid

verfasst von: Naoki Masuyama, Md. Nazrul Islam, Manjeevan Seera, Chu Kiong Loo

Erschienen in: Neural Computing and Applications | Ausgabe 4/2017

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Abstract

Emotional factor plays an important role in communication. In the field of psychology, it is known that memory and emotions are closely related to each other. In this paper, we present the significance of emotional factors to associative memory in communication and apply it on human–robot interaction problems. Emotional models for the robot partner are developed, and an interactive robot system with a complex-valued multi-directional associative memory model is proposed. We utilize multi-modal information such as object, gesture, voice, and facial expressions to associate the relationships in associative memory, and generate the emotional information for the robot partner. As a result, the robot partner is able to perform various actions depending on the emotional factors. Results from the interactive experiments indicate possibility of suitable information for communication space being provided from the robot partner.
Vorheriger Artikel Robust dissipativity and passivity based state estimation for discrete-time stochastic Markov jump neural networks with discrete and distributed time-varying delays
Nächster Artikel Breast cancer diagnosis using GA feature selection and Rotation Forest

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Literatur
1.
Pfeifer R, Scheier C (1999) Understanding intelligence. The MIT Press, Cambridge
2.
Gregory RL (1998) The mind. Oxford Univ Press, Oxford
3.
Sperber D, Wilson D (1995) Relevance: communication and cognition. Oxford Univ Press, Oxford
4.
Minsky M (1986) The society of mind. Simon and Schuster, New York
5.
Yorita A, Kubota N (2011) Cognitive development in partner robots for information support to elderly people. IEEE Trans Auton Ment Dev 3(1):64–73CrossRef
6.
Zheng K, Glas DF, Kanda T, Ishiguro H, Hagita N (2013) Designing and implementing a human–robot team for social interactions. IEEE Trans Syst Man Cybern Syst 43(4):843–859CrossRef
7.
Toris R, Kent D, Chernova S (2014) The robot management system: A framework for conducting human–robot interaction studies through crowdsourcing. J Hum Robot Interact 3(2):25–49CrossRef
8.
Bechara A, Damasio H, Damasio AR (2000) Emotion, decision making and the orbitofrontal cortex. Cereb Cortex 10(3):295–307CrossRef
9.
Reisberg DE, Hertel PE (2004) Memory and emotion. Oxford University Press, OxfordCrossRef
10.
Ekkekakis P (2013) The measurement of affect, mood, and emotion: a guide for health-behavioral research. Cambridge University Press, CambridgeCrossRef
11.
12.
Rosenblatt F (1958) The perceptron: a probabilistic model for information storage and organization in the brain. Psychol Rev 65(6):386CrossRef
13.
Aizenberg N, Ivaskiv YL, Pospelov D, Hudiakov G (1973) Multiple-valued threshold functions. II. Synthesis of the multi-valued threshold elements. Kibernetika (Cybernetics) 1:53–66
14.
Hopfield JJ (1982) Neural networks and physical systems with emergent collective computational abilities. Proc Natl Acad Sci 79(8):2554–2558MathSciNetCrossRef
15.
Kosko B (1987) Constructing an associative memory. Byte 12(10):137–144
16.
Hagiwara M (1990) Multidirectional associative memory. In: International joint conference on neural networks, vol 1, pp 3–6
17.
Noest A (1988) Discrete-state phasor neural networks. Phys Rev A 38(4):2196–2199CrossRef
18.
Jankowski S, Lozowski A, Zurada J (1996) Complex-valued multistate neural associative memory. IEEE Trans Neural Netw 7(6):1491–1496CrossRef
19.
Donq-Liang L, Wen-June W (1998) A multivalued bidirectional associative memory operating on a complex domain. Neural Netw 11(9):1623–1635CrossRef
20.
Kobayashi M, Yamazaki H (2005) Complex-valued multidirectional associative memory. IEEJ Trans Electron Inf Syst 125:1290–1295
21.
22.
Kitahara M, Kobayashi M (2014) Projection rule for rotor hopfield neural networks. IEEE Trans Neural Netw Learn Syst 25(7):1298–1307CrossRef
23.
Oh H, Kothari SC (1994) Adaptation of the relaxation method for learning in bidirectional associative memory. IEEE Trans Neural Netw 5(4):576–583CrossRef
24.
Shimizu Y, Osana Y (2010) Chaotic complex-valued multidirectional associative memory. In: IASTED artificial intelligence and applications
25.
Yoshida A, Osana Y (2011) Chaotic complex-valued multidirectional associative memory with variable scaling factor. In: Artificial neural networks and machine learning—ICANN 2011. Springer, pp 266–274
26.
Gandhi V, Prasad G, Coyle D, Behera L, McGinnity T (2014) Quantum neural network-based eeg filtering for a brain–computer interface. IEEE Trans Neural Netw Learn Syst 25(2):278–288CrossRef
27.
Chen C, Dong D, Li H, Chu J, Tarn T (2014) Fidelity-based probabilistic q-learning for control of quantum systems. IEEE Trans Neural Netw Learn Syst 25(5):920–933CrossRef
28.
29.
Ekman P (1992) An argument for basic emotions. Cognit Emot 6(3–4):169–200CrossRef
30.
Russell JA (1980) A circumplex model of affect. J Personal Soc Psychol 39(6):1161CrossRef
31.
Han MJ, Lin CH, Song KT (2013) Robotic emotional expression generation based on mood transition and personality model. IEEE Trans Cybern 43(4):1290–1303CrossRef
32.
Schneider M, Adamy J (2014) Towards modelling affect and emotions in autonomous agents with recurrent fuzzy systems. In: 2014 IEEE international conference on systems, man and cybernetics (SMC). IEEE, pp 31–38
33.
Russell JA, Barrett LF (1999) Core affect, prototypical emotional episodes, and other things called emotion: dissecting the elephant. J Personal Soc Psychol 76(5):805CrossRef
34.
Ortony A (1990) The cognitive structure of emotions. Cambridge University Press, Cambridge
35.
36.
LeDoux JE (1994) Emotion, memory and the brain. Sci Am 270(6):50–57CrossRef
37.
38.
Friedman HS, Riggio RE (1981) Effect of individual differences in nonverbal expressiveness on transmission of emotion. J Nonverbal Behav 6(2):96–104CrossRef
39.
Cristinacce D, Cootes T (2008) Automatic feature localisation with constrained local models. Pattern Recognit 41(10):3054–3067CrossRefMATH
40.
Nuevo J, Bergasa LM, Jim’enez P (2010) RSMAT: robust simultaneous modeling and tracking. Pattern Recognit Lett 31(16):2455–2463CrossRef
41.
Dawood F, Loo CK, Chin WH (2013) Incremental on-line learning of human motion using gaussian adaptive resonance hidden markov model. In: The 2013 international joint conference on neural networks (IJCNN). IEEE, pp 1–7
42.
Smith SM, Petty RE (1995) Personality moderators of mood congruency effects on cognition: the role of self-esteem and negative mood regulation. J Personal Soc Psychol 68(6):1092CrossRef
43.
Kubota N, Toda Y (2012) Multimodal communication for human-friendly robot partners in informationally structured space. IEEE Trans Syst Man Cybern Part C Appl Rev 42(6):1142–1151CrossRef
44.
Lee A, Kawahara T (2009) Recent development of open-source speech recognition engine Julius. In: Proceedings: APSIPA ASC 2009, pp 131–137
45.
Webb J, Ashley J (2012) Beginning Kinect Programming with the Microsoft Kinect SDK. Apress, New YorkCrossRef
46.
Saragih JM, Lucey S, Cohn JF (2011) Deformable model fitting by regularized landmark mean-shift. Int J Comput Vis 91(2):200–215MathSciNetCrossRefMATH
47.
Cootes TF, Taylor CJ (1992) Active shape models—‘smart snakes’. In: BMVC92. Springer, pp 266–275
48.
Di Stefano L, Mattoccia S, Tombari F (2005) ZNCC-based template matching using bounded partial correlation. Pattern Recognit Lett 26(14):2129–2134CrossRef
49.
Kanaujia A, Huang Y, Metaxas D (2006) Tracking facial features using mixture of point distribution models. In: Computer vision, graphics and image processing. Springer, pp 492–503
50.
Rychlak JF (1973) Introduction to personality and psychotherapy: A theory-construction approach. Houghton Mifflin, Boston
51.
Mischel W (1993) Introduction to personality, vol 250. London
Metadaten
Titel
Application of emotion affected associative memory based on mood congruency effects for a humanoid
verfasst von
Naoki Masuyama
Md. Nazrul Islam
Manjeevan Seera
Chu Kiong Loo
Publikationsdatum
19.11.2015
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 4/2017
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-015-2102-x

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