MotivEn: Motivational engine with sub-goal identification for autonomous robots

This paper presents an initial integrated approximation to the complete problem of robot motivation in continuous domains in terms of how to adaptively combine intrinsic and extrinsic motivations into an integrated motivational engine, called MotivEn. It allows an autonomous robot to find goals and decompose them into sub-goals that can be chained to facilitate achieving the final goal. MotivEn is based on an evolutionarily learnt value function in continuous domains where exploration and exploitation, as well as its decomposition into sub-value functions, is autonomously achieved.

[1]  Stéphane Doncieux,et al.  Behavioral diversity measures for Evolutionary Robotics , 2010, IEEE Congress on Evolutionary Computation.

[2]  Shie Mannor,et al.  Q-Cut - Dynamic Discovery of Sub-goals in Reinforcement Learning , 2002, ECML.

[3]  Pierre-Yves Oudeyer,et al.  What is Intrinsic Motivation? A Typology of Computational Approaches , 2007, Frontiers Neurorobotics.

[4]  Shie Mannor,et al.  Dynamic abstraction in reinforcement learning via clustering , 2004, ICML.

[5]  David Vernon,et al.  A Roadmap for Cognitive Development in Humanoid Robots , 2011, Cognitive Systems Monographs.

[6]  G. Konidaris,et al.  Sensorimotor abstraction selection for efficient, autonomous robot skill acquisition , 2008, 2008 7th IEEE International Conference on Development and Learning.

[7]  E. Deci,et al.  Intrinsic and Extrinsic Motivations: Classic Definitions and New Directions. , 2000, Contemporary educational psychology.

[8]  Shaul Markovitch,et al.  Learning Novel Domains Through Curiosity and Conjecture , 1989, IJCAI.

[9]  Andrew G. Barto,et al.  Automatic Discovery of Subgoals in Reinforcement Learning using Diverse Density , 2001, ICML.

[10]  Andrew G. Barto,et al.  Intrinsic Motivation and Reinforcement Learning , 2013, Intrinsically Motivated Learning in Natural and Artificial Systems.

[11]  Richard S. Sutton,et al.  Reinforcement learning architectures for animats , 1991 .

[12]  Marco Mirolli,et al.  Deciding Which Skill to Learn When: Temporal-Difference Competence-Based Intrinsic Motivation (TD-CB-IM) , 2013, Intrinsically Motivated Learning in Natural and Artificial Systems.

[13]  Andrés Faiña,et al.  Multilevel Darwinist Brain (MDB): Artificial Evolution in a Cognitive Architecture for Real Robots , 2010, IEEE Transactions on Autonomous Mental Development.

[14]  Christoph Salge,et al.  Approximation of Empowerment in the continuous Domain , 2013, Adv. Complex Syst..