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The integration of reasoning, learning, and decision-making is key to build more general artificial intelligence systems.
Learning algorithms via neural logic networks
Ali Payani and Faramarz Fekri · 1904
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Inductive logic programming via differentiable deep neural logic networks
Ali Payani and Faramarz Fekri · 1906
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A Markovian decision process
Richard Bellman · 1957
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Inductive logic programming
Stephen Muggleton · 1991
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Simple statistical gradient-following algorithms for connectionist reinforcement learning
Ronald J. Williams · 1992
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Actor-critic algorithms
Vijay Konda and John Tsitsiklis · 2000
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Relational reinforcement learning
Sašo Džeroski, Luc De Raedt, and Kurt Driessens · 2001
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Relational reinforcement learning : An overview
Prasad Tadepalli, Robert Givan, and Kurt Driessens · 2004
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Problog: a probabilistic prolog and its application in link discovery
Luc De Raedt, Angelika Kimmig, and Hannu Toivonen · 2007
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Solving relational and first-order logical markov decision processes: A survey
Martijn van Otterlo · 2012
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Learning phrase representations using rnn encoder-decoder for statistical machine translation
Kyunghyun Cho, Bart van Merrienboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio · 2014
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Logic programming
Robert A Kowalski · 2014
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Trust region policy optimization
J. Schulman, S. Levine, P. Abbeel, M.I. Jordan, and P. Moritz · 2015
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End-to-end memory networks
Sainbayar Sukhbaatar, Arthur Szlam, Jason Weston, and Rob Fergus · 2015
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Statistical Relational AI: Logic, Probability and Computation
Luc De Raedt, Kristian Kersting, Sriraam Natarajan, and David Poole · 2016
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Hybrid computing using a neural network with dynamic external memory
A Graves, G Wayne, M Reynolds, T Harley, I Danihelka, A Grabska-Barwińska, SG Colmenarejo, E Grefenstette, T Ramalho, J Agapiou, and et al · 2016
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Continuous control with deep reinforcement learning
Timothy P. Lillicrap, Jonathan J. Hunt, Alexander Pritzel, Nicolas Heess, Tom Erez, Yuval Tassa, David Silver, and Daan Wierstra · 2016
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Asynchronous methods for deep reinforcement learning
Volodymyr Mnih, Adrià Puigdomènech Badia, Mehdi Mirza, Alex Graves, Timothy P. Lillicrap, Tim Harley, David Silver, and Koray Kavukcuoglu · 2016
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High-dimensional continuous control using generalized advantage estimation
Deepproblog: Neural probabilistic logic programming
Robin Manhaeve, Sebastijan Dumančić, Angelika Kimmig, Thomas Demeester, and Luc De Raedt · 2018
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Deep learning: A critical appraisal
Gary Marcus · 2018
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Reinforcement learning: An introduction
Richard S Sutton and Andrew G Barto · 2018
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Neural Logic Machines
Honghua Dong, Jiayuan Mao, Tian Lin, Chong Wang, Lihong Li, and Denny Zhou · 2019
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Neural-symbolic computing: An effective methodology for principled integration of machine learning and reasoning
Artur d’Avila Garcez, Marco Gori, Luis C. Lamb, Luciano Serafini, Michael Spranger, and Son N. Tran · 2019
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Neural Logic Reinforcement Learning
Zhengyao Jiang and Shan Luo · 2019
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J. Schulman, P. Moritz, S. Levine, M.I. Jordan, and P. Abbeel · 2016
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Neural-symbolic learning and reasoning: A survey and interpretation
Tarek R. Besold, Artur d’Avila Garcez, Sebastian Bader, Howard Bowman, Pedro Domingos, Pascal Hitzler, Kai-Uwe Kuehnberger, Luis C. Lamb, Daniel Lowd, Priscila Machado Vieira Lima, Leo de Penning, Gadi Pinkas, Hoifung Poon, and Gerson Zaverucha · 2017
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Categorical reparameterization with gumbel-softmax
Eric Jang, Shixiang Gu, and Ben Poole · 2017
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Building machines that learn and think like people
Brenden M. Lake, Tomer D. Ullman, Joshua B. Tenenbaum, and Samuel J. Gershman · 2017
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Proximal Policy Optimization Algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
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Differentiable learning of logical rules for knowledge base reasoning
Fan Yang, Zhilin Yang, and William W. Cohen · 2017
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Learning explanatory rules from noisy data
Richard Evans and Edward Grefenstette · 2018
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Explainable artificial intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible ai
Alejandro Barredo Arrieta, Natalia Díaz-Rodríguez, Javier Del Ser, Adrien Bennetot, Siham Tabik, Alberto Barbado, Salvador Garcia, Sergio Gil-Lopez, Daniel Molina, Richard Benjamins, and et al · 2020
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Turning 30: New ideas in inductive logic programming
Andrew Cropper, Sebastijan Dumančić, and Stephen H. Muggleton · 2020
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From Statistical Relational to Neuro-Symbolic Artificial Intelligence
Luc de Raedt, Sebastijan Dumančić, Robin Manhaeve, and Giuseppe Marra · 2020
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Ali Payani and Faramarz Fekri · 2020
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Learn to explain efficiently via neural logic inductive learning
Yuan Yang and Le Song · 2020
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Neuro-symbolic hierarchical rule induction
Claire Glanois, Zhaohui Jiang, Xuening Feng, Paul Weng, Matthieu Zimmer, Dong Li, Wulong Liu, and Jianye Hao · 2022
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