Lifelong robot learning

[1]  Tom M. Mitchell,et al.  Explanation-based learning for mobile-robot perception , 1997 .

[2]  Thrun,et al.  Explanation-Based Learning for Mobile Robot , 1996 .

[3]  Sebastian Thrun,et al.  An approach to learning mobile robot navigation , 1995, Robotics Auton. Syst..

[4]  Sebastian Thrun,et al.  Learning One More Thing , 1994, IJCAI.

[5]  Tom Michael Mitchell.  Learning Analytically and Inductively , 1995 .

[6]  Sebastian Thrun,et al.  A lifelong learning perspective for mobile robot control , 1994, Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'94).

[7]  Sebastian Thrun,et al.  Learning to Play the Game of Chess , 1994, NIPS.

[8]  Sebastian Thrun,et al.  Integrating Inductive Neural Network Learning and Explanation-Based Learning , 1993, IJCAI.

[9]  Rich Caruana,et al.  Multitask Learning: A Knowledge-Based Source of Inductive Bias , 1993, ICML.

[10]  Sebastian Thrun,et al.  Explanation Based Learning: A Comparison of Symbolic and Neural Network Approaches , 1993, ICML.

[11]  Sebastian Thrun,et al.  Exploration and model building in mobile robot domains , 1993, IEEE International Conference on Neural Networks.

[12]  Lorien Y. Pratt,et al.  Discriminability-Based Transfer between Neural Networks , 1992, NIPS.

[13]  Sebastian Thrun,et al.  Explanation-Based Neural Network Learning for Robot Control , 1992, NIPS.

[14]  Geoffrey E. Hinton,et al.  Feudal Reinforcement Learning , 1992, NIPS.

[15]  Lonnie Chrisman,et al.  Reinforcement Learning with Perceptual Aliasing: The Perceptual Distinctions Approach , 1992, AAAI.

[16]  Richard S. Sutton,et al.  Adapting Bias by Gradient Descent: An Incremental Version of Delta-Bar-Delta , 1992, AAAI.

[17]  Donald A. Sofge,et al.  Handbook of Intelligent Control: Neural, Fuzzy, and Adaptive Approaches , 1992 .

[18]  Long Lin,et al.  Memory Approaches to Reinforcement Learning in Non-Markovian Domains , 1992 .

[19]  Sebastian Thrun,et al.  The role of exploration in learning control , 1992 .

[20]  N. Chater,et al.  Proceedings of the fourteenth annual conference of the cognitive science society , 1992 .

[21]  D. Sofge.  THE ROLE OF EXPLORATION IN LEARNING CONTROL , 1992 .

[22]  Satinder P. Singh,et al.  The Efficient Learning of Multiple Task Sequences , 1991, NIPS.

[23]  Yann LeCun,et al.  Tangent Prop - A Formalism for Specifying Selected Invariances in an Adaptive Network , 1991, NIPS.

[24]  Benjamin Kuipers,et al.  A robot exploration and mapping strategy based on a semantic hierarchy of spatial representations , 1991, Robotics Auton. Syst..

[25]  Tom Bylander,et al.  Complexity Results for Planning , 1991, IJCAI.

[26]  Lawrence Birnbaum,et al.  Proceedings of the eighth international workshop on Machine learning , 1991 .

[27]  Ming Tan,et al.  Learning a Cost-Sensitive Internal Representation for Reinforcement Learning , 1991, ML.

[28]  Sridhar Mahadevan,et al.  Scaling Reinforcement Learning to Robotics by Exploiting the Subsumption Architecture , 1991, ML.

[29]  Christopher G. Atkeson,et al.  Using locally weighted regression for robot learning , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[30]  Pattie Maes,et al.  Designing autonomous agents: Theory and practice from biology to engineering and back , 1990, Robotics Auton. Syst..

[31]  Richard S. Sutton,et al.  Integrated Architectures for Learning, Planning, and Reacting Based on Approximating Dynamic Programming , 1990, ML.

[32]  S. C. Suddarth,et al.  Rule-Injection Hints as a Means of Improving Network Performance and Learning Time , 1990, EURASIP Workshop.

[33]  Bartlett W. Mel,et al.  Murphy: A neurally-inspired connectionist approach to learning and performance in vision-based robot motion planning , 1990 .

[34]  Michael C. Mozer,et al.  Discovering the Structure of a Reactive Environment by Exploration , 1990, Neural Computation.

[35]  Andrew W. Moore,et al.  Efficient memory-based learning for robot control , 1990 .

[36]  Richard S. Sutton,et al.  Learning and Sequential Decision Making , 1989 .

[37]  Rodney A. Brooks,et al.  A Robot that Walks; Emergent Behaviors from a Carefully Evolved Network , 1989, Neural Computation.

[38]  C. Watkins.  Learning from delayed rewards , 1989 .

[39]  Michael I. Jordan,et al.  Generic constraints on underspecified target trajectories , 1989, International 1989 Joint Conference on Neural Networks.

[40]  John Canny,et al.  The complexity of robot motion planning , 1988 .

[41]  Hans P. Moravec.  Sensor Fusion in Certainty Grids for Mobile Robots , 1988, AI Mag..

[42]  Dean Pomerleau,et al.  ALVINN, an autonomous land vehicle in a neural network , 2015 .

[43]  Ronald L. Rivest,et al.  Diversity-based inference of finite automata , 1994, 28th Annual Symposium on Foundations of Computer Science (sfcs 1987).

[44]  Ronald L. Rivest,et al.  Diversity-Based Inference of Finite Automata (Extended Abstract) , 1987, FOCS.

[45]  Alberto Elfes,et al.  Sonar-based real-world mapping and navigation , 1987, IEEE J. Robotics Autom..

[46]  이종원,et al.  Explanation - Based Generalization 의 문제점 및 이의 해결방안 , 1986 .

[47]  Micha Sharir,et al.  Planning, geometry, and complexity of robot motion , 1986 .

[48]  Geoffrey E. Hinton,et al.  Learning internal representations by error propagation , 1986 .

[49]  Richard S. Sutton,et al.  Temporal credit assignment in reinforcement learning , 1984 .

[50]  R. Bellman.  Dynamic Programming , 1957, Science.

[51]  R. E. Kalman,et al.  A New Approach to Linear Filtering and Prediction Problems , 2002 .

[52]  Arthur L. Samuel,et al.  Some Studies in Machine Learning Using the Game of Checkers , 1967, IBM J. Res. Dev..