Research of an Intrinsic Motivation Based on the Tropism

Abstract

Abstract: An intrinsic motivation system based on the tropism is presented for the behavioral cognitive problem on the intelligent robot, and the learning evaluation mechanisms and the sensorimotor coordination mechanism are mainly analyzed. The intrinsic motivation is used to build a motion neurocognitive system for a desktop robot realising the learning and cognitive processes like the biological negative phototaxis behavior. The simulation results show the effectiveness of the system.

Key words: , tropism； intrinsic motivation； intelligent robot； negative phototaxis

CLC Number:

DAI Lizhen. Research of an Intrinsic Motivation Based on the Tropism[J]. Journal of Shanghai Jiaotong University, 2017, 51(7): 892-896.

References

［1］DECI E L, RYAN R M. Intrinsic motivation［M］. New York: Plenum Press, 1975.
［2］WHITE R W. Motivation reconsidered: The concept of competence［J］. Psychological Review, 1959, 66(5): 297333.
［3］DAYAN P, BALLEINE B W. Reward, motivation, and reinforcement learning［J］. Neuron, 2002, 36(2): 285298.
［4］OUDEYER P Y, KAPLAN F. What is intrinsic motivation? A typology of computational approaches［J］. Frontiers in Neurorobotics, 2007, 1(6): 114.
［5］OUDEYER P Y, KAPLAN F, HAFNER V V. Intrinsic motivation systems for autonomous mental development［J］. IEEE Transactions on Evolutionary Computation, 2007, 11(2): 265286.
［6］BARANES A, OUDEYER P Y. RIAC: Robust intrinsically motivated exploration and active learning［J］. IEEE Transactions on Autonomous Mental Development, 2009, 1(3): 155169.
［7］BARANES A, OUDEYER P. Maturationallyconstrained competencebased intrinsically motivated learning［C］∥Proceedings of IEEE 9th International Conference on Development and Learning (ICDL). New York, USA: IEEE, 2010: 197203.
［8］SINGH S, LEWIS R L, BARTO A G, et al. Intrinsically motivated reinforcement learning: An evolutionary perspective［J］. IEEE Transactions on Autonomous Mental Development, 2010, 2(2): 7082.
［9］VIGORITO C M, BARTO A G. Intrinsically motivated hierarchical skill learning in structured environments［J］. IEEE Transactions on Autonomous Mental Development, 2010, 2(2): 132143.
［10］BARANES A, OUDEYER P Y. Active learning of inverse models with intrinsically motivated goal exploration in robots［J］. Robotics and Autonomous Systems, 2013, 61(1): 4973.
［11］NGUYEN S M, OUDEYER P Y. Socially guided intrinsic motivation for robot learning of motor skills［J］. Autonomous Robots, 2014, 36(3): 273294.
［12］WENG J, LUWANG T, LU H, et al. A multilayer inplace learning network for development of general invariances［J］. International Journal of Humanoid Robotics, 2007, 4(2): 281320.
［13］江济良, 屠大维, 张国栋, 等. 基于认知模型的室内移动服务机器人人机耦合协同作业机制［J］. 智能系统学报, 2012, 7(3): 251258.
JIANG Jiliang, TU Dawei, ZHANG Guodong, et al. A mechanism of humanrobot coupling and collaborative operation for indoor mobile service robots based on a cognitive architecture model［J］. CAAL Transactions on Intelligent Systems, 2012, 7(3): 251258.
［14］陈世佳, 尹东, 张荣, 等. 认知推理的家庭服务机器人演示学习研究［J］. 小型微型计算机系统, 2013, 34(6): 14411445.
CHEN Shijia, YIN Dong, ZHANG Rong, et al. Research in learning from demonstration based on cognitive reasoning for family service robot［J］. Journal of Chinese Computer Systems, 2013, 34(6): 14411445.
［15］BERLYNE D E. Conflict, arousal, and curiosity［M］. New York: McGrawHill. 1960.

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