Intrinsically motivated model learning for developing curious robots

[1]  Pierre-Yves Oudeyer,et al.  Exploration in Model-based Reinforcement Learning by Empirically Estimating Learning Progress , 2012, NIPS.

[2]  Peter Stone,et al.  Intrinsically motivated model learning for a developing curious agent , 2012, 2012 IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL).

[3]  Richard L. Lewis,et al.  Strong mitigation: nesting search for good policies within search for good reward , 2012, AAMAS.

[4]  Michael L. Littman,et al.  Bandit-Based Planning and Learning in Continuous-Action Markov Decision Processes , 2012, ICAPS.

[5]  Peter Stone,et al.  RTMBA: A Real-Time Model-Based Reinforcement Learning Architecture for robot control , 2011, 2012 IEEE International Conference on Robotics and Automation.

[6]  Sam Devlin,et al.  An Empirical Study of Potential-Based Reward Shaping and Advice in Complex, Multi-Agent Systems , 2011, Adv. Complex Syst..

[7]  Ana Paiva,et al.  Emotion-Based Intrinsic Motivation for Reinforcement Learning Agents , 2011, ACII.

[8]  Richard L. Lewis,et al.  Optimal Rewards versus Leaf-Evaluation Heuristics in Planning Agents , 2011, AAAI.

[9]  Peter Stone,et al.  Structure Learning in Ergodic Factored MDPs without Knowledge of the Transition Function's In-Degree , 2011, ICML.

[10]  Rémi Munos,et al.  Pure exploration in finitely-armed and continuous-armed bandits , 2011, Theor. Comput. Sci..

[11]  Michael L. Littman,et al.  Sample-Based Planning for Continuous Action Markov Decision Processes , 2011, ICAPS.

[12]  Andrew G. Barto,et al.  Competence progress intrinsic motivation , 2010, 2010 IEEE 9th International Conference on Development and Learning.

[13]  Peter Stone,et al.  Real time targeted exploration in large domains , 2010, 2010 IEEE 9th International Conference on Development and Learning.

[14]  Richard L. Lewis,et al.  Internal Rewards Mitigate Agent Boundedness , 2010, ICML.

[15]  Pierre-Yves Oudeyer,et al.  Guest Editorial Active Learning and Intrinsically Motivated Exploration in Robots: Advances and Challenges , 2010, IEEE Trans. Auton. Ment. Dev..

[16]  Andrew G. Barto,et al.  Intrinsically Motivated Hierarchical Skill Learning in Structured Environments , 2010, IEEE Transactions on Autonomous Mental Development.

[17]  Richard L. Lewis,et al.  Intrinsically Motivated Reinforcement Learning: An Evolutionary Perspective , 2010, IEEE Transactions on Autonomous Mental Development.

[18]  Pierre-Yves Oudeyer,et al.  R-IAC: Robust Intrinsically Motivated Exploration and Active Learning , 2009, IEEE Transactions on Autonomous Mental Development.

[19]  Morgan Quigley,et al.  ROS: an open-source Robot Operating System , 2009, ICRA 2009.

[20]  Todd Hester and Peter Stone An Empirical Comparison of Abstraction in Models of Markov Decision Processes , 2009 .

[21]  Michael L. Littman,et al.  Efficient Structure Learning in Factored-State MDPs , 2007, AAAI.

[22]  Michael L. Littman,et al.  Efficient Reinforcement Learning with Relocatable Action Models , 2007, AAAI.

[23]  Andrew G. Barto,et al.  Active Learning of Dynamic Bayesian Networks in Markov Decision Processes , 2007, SARA.

[24]  Peter Stone,et al.  Model-based function approximation in reinforcement learning , 2007, AAMAS '07.

[25]  Andrew G. Barto,et al.  Building Portable Options: Skill Transfer in Reinforcement Learning , 2007, IJCAI.

[26]  Csaba Szepesvári,et al.  Bandit Based Monte-Carlo Planning , 2006, ECML.

[27]  Andrew G. Barto,et al.  An intrinsic reward mechanism for efficient exploration , 2006, ICML.

[28]  Olivier Sigaud,et al.  Learning the structure of Factored Markov Decision Processes in reinforcement learning problems , 2006, ICML.

[29]  Richard S. Sutton,et al.  Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.

[30]  Nuttapong Chentanez,et al.  Intrinsically Motivated Reinforcement Learning , 2004, NIPS.

[31]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[32]  J. Ross Quinlan,et al.  Induction of Decision Trees , 1986, Machine Learning.

[33]  Dale Schuurmans,et al.  Algorithm-Directed Exploration for Model-Based Reinforcement Learning in Factored MDPs , 2002, ICML.

[34]  Ronen I. Brafman,et al.  R-MAX - A General Polynomial Time Algorithm for Near-Optimal Reinforcement Learning , 2001, J. Mach. Learn. Res..

[35]  Andrew Y. Ng,et al.  Policy Invariance Under Reward Transformations: Theory and Application to Reward Shaping , 1999, ICML.

[36]  Preben Alstrøm,et al.  Learning to Drive a Bicycle Using Reinforcement Learning and Shaping , 1998, ICML.

[37]  Richard S. Sutton,et al.  Introduction to Reinforcement Learning , 1998 .

[38]  Ben J. A. Kröse,et al.  Learning from delayed rewards , 1995, Robotics Auton. Syst..

[39]  Jürgen Schmidhuber,et al.  Curious model-building control systems , 1991, [Proceedings] 1991 IEEE International Joint Conference on Neural Networks.