TY - GEN
T1 - Looking Back and Ahead
T2 - 9th Joint IEEE International Conference on Development and Learning and Epigenetic Robotics, ICDL-EpiRob 2019
AU - Murata, Shingo
AU - Sawa, Hiroki
AU - Sugano, Shigeki
AU - Ogata, Tetsuya
N1 - Funding Information:
This work was supported in part by JST CREST (JPMJCR15E3); JSPS KAKENHI (JP17K12754 and JP19K20364), and Research Institute for Science and Engineering, Waseda University.
Publisher Copyright:
© 2019 IEEE.
PY - 2019/8
Y1 - 2019/8
N2 - Adaptation and planning are crucial for both biological and artificial agents. In this study, we treat these as an inference problem that we solve using a gradient-based optimization approach. We propose adaptation and planning by gradient descent (APGraDe), a gradient-based computational framework with a hierarchical recurrent neural network (RNN) for adaptation and planning. This framework computes (counterfactual) prediction errors by looking back on past situations based on actual observations and by looking ahead to future situations based on preferred observations (or goal). The internal state of the higher level of the RNN is optimized in the direction of minimizing these errors. The errors for the past contribute to the adaptation while errors for the future contribute to the planning. The proposed APGraDe framework is implemented in a humanoid robot and the robot performs a ball manipulation task with a human experimenter. Experimental results show that given a particular preference, the robot can adapt to unexpected situations while pursuing its own preference through the planning of future actions.
AB - Adaptation and planning are crucial for both biological and artificial agents. In this study, we treat these as an inference problem that we solve using a gradient-based optimization approach. We propose adaptation and planning by gradient descent (APGraDe), a gradient-based computational framework with a hierarchical recurrent neural network (RNN) for adaptation and planning. This framework computes (counterfactual) prediction errors by looking back on past situations based on actual observations and by looking ahead to future situations based on preferred observations (or goal). The internal state of the higher level of the RNN is optimized in the direction of minimizing these errors. The errors for the past contribute to the adaptation while errors for the future contribute to the planning. The proposed APGraDe framework is implemented in a humanoid robot and the robot performs a ball manipulation task with a human experimenter. Experimental results show that given a particular preference, the robot can adapt to unexpected situations while pursuing its own preference through the planning of future actions.
KW - active inference
KW - free-energy principle
KW - planning as inference
KW - prediction error minimization
KW - predictive coding
KW - recurrent neural network
UR - http://www.scopus.com/inward/record.url?scp=85073672024&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85073672024&partnerID=8YFLogxK
U2 - 10.1109/DEVLRN.2019.8850693
DO - 10.1109/DEVLRN.2019.8850693
M3 - Conference contribution
AN - SCOPUS:85073672024
T3 - 2019 Joint IEEE 9th International Conference on Development and Learning and Epigenetic Robotics, ICDL-EpiRob 2019
SP - 151
EP - 156
BT - 2019 Joint IEEE 9th International Conference on Development and Learning and Epigenetic Robotics, ICDL-EpiRob 2019
A2 - Aly, Amir
A2 - Bicho, Estela
A2 - Boucenna, Sofiane
A2 - Castro da Silva, Bruno
A2 - Chetouani, Mohamed
A2 - del Pobil, Angel P.
A2 - Diard, Julien
A2 - Doncieux, Stephane
A2 - Goksun, Tilbe
A2 - Grimminger, Angela
A2 - Guerin, Frank
A2 - Hagiwara, Yoshinobu
A2 - Jamone, Lorenzo
A2 - Kalkan, Sinan
A2 - Lara, Bruno
A2 - Moulin-Frier, Clement
A2 - Murata, Shingo
A2 - Nagai, Takayuki
A2 - Nagai, Yukie
A2 - Nomikou, Iris
A2 - Ogino, Masaki
A2 - Oudeyer, Pierre-Yves
A2 - Pereira, Alfredo F.
A2 - Pitti, Alexandre
A2 - Raczaszek-Leonardi, Joanna
A2 - Risi, Sebastian
A2 - Rosman, Benjamin
A2 - Sandamirskaya, Yulia
A2 - Schilling, Malte
A2 - Sciutti, Alessandra
A2 - Shaw, Patricia
A2 - Soltoggio, Andrea
A2 - Spranger, Michael
A2 - Taniguchi, Tadahiro
A2 - Thill, Serge
A2 - Triesch, Jochen
A2 - Ugur, Emre
A2 - Vollmer, Anna-Lisa
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 19 August 2019 through 22 August 2019
ER -