Relational Reinforcement Learning
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[1] Thomas Gärtner,et al. Graph kernels and Gaussian processes for relational reinforcement learning , 2006, Machine Learning.
[2] J. Ross Quinlan,et al. Learning logical definitions from relations , 1990, Machine Learning.
[3] Richard S. Sutton,et al. Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.
[4] Reid G. Simmons,et al. The Effect of Representation and Knowledge on Goal-Directed Exploration with Reinforcement-Learning Algorithms , 2005, Machine Learning.
[5] Saso Dzeroski,et al. Integrating Guidance into Relational Reinforcement Learning , 2004, Machine Learning.
[6] Luc De Raedt,et al. Scaling Up Inductive Logic Programming by Learning from Interpretations , 1999, Data Mining and Knowledge Discovery.
[7] Paul E. Utgoff,et al. Decision Tree Induction Based on Efficient Tree Restructuring , 1997, Machine Learning.
[8] Ivan Bratko,et al. First Order Regression , 1997, Machine Learning.
[9] Manuela M. Veloso,et al. Lazy Incremental Learning of Control Knowledge for Efficiently Obtaining Quality Plans , 1997, Artificial Intelligence Review.
[10] Peter Dayan,et al. Q-learning , 1992, Machine Learning.
[11] Long Ji Lin,et al. Self-improving reactive agents based on reinforcement learning, planning and teaching , 1992, Machine Learning.
[12] Tom M. Mitchell,et al. Explanation-Based Generalization: A Unifying View , 1986, Machine Learning.
[13] J. Ross Quinlan,et al. Induction of Decision Trees , 1986, Machine Learning.
[14] Kurt Driessens,et al. Relational Instance Based Regression for Relational Reinforcement Learning , 2003, ICML.
[15] Saso Dzeroski,et al. Integrating Experimentation and Guidance in Relational Reinforcement Learning , 2002, ICML.
[16] Kurt Driessens,et al. Learning digger using hierarchical reinforcement learning for concurrent goals , 2001 .
[17] Kurt Driessens,et al. Speeding Up Relational Reinforcement Learning through the Use of an Incremental First Order Decision Tree Learner , 2001, ECML.
[18] Doina Precup,et al. Between MDPs and Semi-MDPs: A Framework for Temporal Abstraction in Reinforcement Learning , 1999, Artif. Intell..
[19] Manuela M. Veloso,et al. Team-partitioned, opaque-transition reinforcement learning , 1999, AGENTS '99.
[20] Hendrik Blockeel,et al. Top-Down Induction of First Order Logical Decision Trees , 1998, AI Commun..
[21] Luc De Raedt,et al. Top-Down Induction of Clustering Trees , 1998, ICML.
[22] Luc De Raedt,et al. Using Logical Decision Trees for Clustering , 1997, ILP.
[23] Luc De Raedt,et al. Lookahead and Discretization in ILP , 1997, ILP.
[24] Thomas G. Dietterich. What is machine learning? , 2020, Archives of Disease in Childhood.
[25] Stefan Kramer,et al. Structural Regression Trees , 1996, AAAI/IAAI, Vol. 1.
[26] Eric B. Baum,et al. Toward a Model of Mind as a Laissez-Faire Economy of Idiots , 1996, ICML.
[27] Andrew W. Moore,et al. Reinforcement Learning: A Survey , 1996, J. Artif. Intell. Res..
[28] Claire Nédellec,et al. Declarative Bias in ILP , 1996 .
[29] Raymond J. Mooney,et al. Induction of First-Order Decision Lists: Results on Learning the Past Tense of English Verbs , 1995, J. Artif. Intell. Res..
[30] 金田 重郎,et al. C4.5: Programs for Machine Learning (書評) , 1995 .
[31] Gerald Tesauro,et al. Temporal Difference Learning and TD-Gammon , 1995, J. Int. Comput. Games Assoc..
[32] Pat Langley,et al. Elements of Machine Learning , 1995 .
[33] Luc De Raedt,et al. Inductive Logic Programming: Theory and Methods , 1994, J. Log. Program..
[34] Saso Dzeroski,et al. Inductive Logic Programming: Techniques and Applications , 1993 .
[35] Tom M. Mitchell,et al. Learning by experimentation: acquiring and refining problem-solving heuristics , 1993 .
[36] Leslie Pack Kaelbling,et al. Input Generalization in Delayed Reinforcement Learning: An Algorithm and Performance Comparisons , 1991, IJCAI.
[37] Jaime G. Carbonell,et al. Learning by experimentation: the operator refinement method , 1990 .
[38] Pat Langley,et al. Strategy Acquisition Governed by Experimentation , 1985, ECAI.
[39] Richard Fikes,et al. STRIPS: A New Approach to the Application of Theorem Proving to Problem Solving , 1971, IJCAI.
[40] De,et al. Relational Reinforcement Learning , 2022 .