Artur d’Avila Garcez | City University London

Books Authored

A. S. d'Avila Garcez, L. C. Lamb and D. M. Gabbay. Neural-Symbolic Cognitive Reasoning. Cognitive Technologies, Springer, ISBN 978-3-540-73245-7, 2009.

A. S. d'Avila Garcez, K. Broda and D. M. Gabbay. Neural-Symbolic Learning Systems: Foundations and Applications, Perspectives in Neural Computing, Springer-Verlag, ISBN 1-85233-512-2, 2002.

Books Edited

S. N. Artemov, H. Barringer, A. S. d'Avila Garcez, L. C. Lamb and J. Woods (eds). We Will Show Them: Essays in Honour of Dov Gabbay. Vol.1, International Federation for Computational Logic, College Publications, 2005.

S. N. Artemov, H. Barringer, A. S. d'Avila Garcez, L. C. Lamb and J. Woods (eds). We Will Show Them: Essays in Honour of Dov Gabbay. Vol.2, International Federation for Computational Logic, College Publications, 2005.

Journal Publications

Kwun Ngan, Esma Mansouri-Benssassi, James Phelan, Joseph Townsend, Artur d'Avila Garcez. From Explanation to Intervention: Interactive Knowledge Extraction from Convolutional Neural Networks used in Radiology. PLOS ONE, March 2024.
A. White, K. H. Ngan, J. Phelan, K. Ryan, S. Sadeghi Afgeh, C. Reyes-Aldasoro, A. d'Avila Garcez. Contrastive Counterfactual Visual Explanations with Overdetermination. Machine Learning journal, Springer, April 2023.
A. d'Avila Garcez and L. Lamb. Neurosymbolic AI: The 3rd Wave. Artificial Intelligence Review, Springer, March 2023. Pre-print arXiv:2012.05876, Dec 2020. \url{https://arxiv.org/abs/2012.05876}.
S. Badreddine, A. d'Avila Garcez, L. Serafini and M. Spranger. Logic Tensor Networks. Artificial Intelligence, Vol. 303, Feb 2022.
C. Percy, S. Dragicevic, S. Sarkar and A. d'Avila Garcez. Accountability in AI: From Principles to Industry-specific Accreditation. AI Communications 34(3):181-196, 2021.
Son Tran, Artur d'Avila Garcez, Tillman Weyde, Qing Zhang, Mohan Karunanithi, Jie Yin. Sequence Classification Restricted Boltzmann Machines with Gated Units. IEEE Transactions on Neural Networks and Learning Systems. Dec 2019.
T. Besold, A. S. d'Avila Garcez, K. Stenning, L. van der Torre and M. van Lambalgen. Reasoning in Non-Probabilistic Uncertainty: Logic Programming and Neural-Symbolic Computing as Examples. Minds and Machines, Springer. DOI:10.1007/s11023-017-9428-3, March 2017.
S. Tran and A. S. d'Avila Garcez. Deep Logic Networks: Inserting and Extracting Knowledge from Deep Belief Networks. IEEE Transactions on Neural Networks and Learning Systems. DOI: 10.1109/TNNLS.2016.2603784, November 2016.
H. Ali, S. Tran, E. Benetos and A. S. d'Avila Garcez. Speaker Recognition with Hybrid Features from a Deep Belief Network. Neural Computing and Applications, Springer, DOI:10.1007/s00521-016-2501-7, August 2016.
C. Percy, M. Franca, S. Dragievic and A. S. d'Avila Garcez. Predicting Online Gambling Self-Exclusion: An Analysis of the Performance of Supervised Machine Learning Models. International Gambling Studies, DOI:10.1080/14459795.2016.1151913, March 2016.
A. Forechi, A. F. De Souza, J. de Oliveira Neto, E. de Aguiar, C. Badue, A. S. d'Avila Garcez, T. Oliveira-Santos. Fat-Fast VG-RAM WNN: A High Performance Approach, Neurocomputing 183:56-69, March 2016.
H. Ali, A. S. d'Avila Garcez, S. Tran, X. Zhou and K. Iqbal. Unimodal Late Fusion for NIST i-vector Challenge on Speaker Detection, IEEE Electronics Letters 50(15):1098-1100, July 2014.
A. S. d'Avila Garcez, D. M. Gabbay and L. C. Lamb. A Neural Cognitive Model of Argumentation with Application to Legal Inference and Decision Making, Journal of Applied Logic 12(2):109-127, Elsevier, June 2014.
M. Franca, G. Zaverucha and A. S. d'Avila Garcez. Fast Relational Learning using Bottom Clause Propositionalization with Artificial Neural Networks, Machine Learning 94(1):81-104, Springer, 2014.
V. Agrawal, J. Baier, K. Bekris, Y. Chen, A. S. d'Avila Garcez, P. Hitzler, P. Haslum, D. Jannach, E. Law, F. Lecue, L. C. Lamb, C. Matuszek, H. Palacios, B. Srivastava, L. Shastri, N. Sturtevant, R. Stern, S. Tellex and S. Vassos. Reports of the AAAI 2012 Conference Workshops, AI Magazine 33(4):119, 2012.

R. V. Borges, A. S. d'Avila Garcez and L. C. Lamb. Learning and Representing Temporal Knowledge in Recurrent Networks. IEEE Transactions on Neural Networks 22(12):2409 - 2421, December 2011.

D. W. Aha, M. Boddy, V. Bulitko, A. S. d'Avila Garcez, P. Doshi, S. Edelkamp, C. Geib, P. Gmytrasiewicz, R. P. Goldman, P. Hitzler, C. Isbell, D. Josyula, L. P. Kaelbling, K. Kersting, M. Kunda, L. C. Lamb, B. Marthi, K. McGreggor, V. Nastase, G. Provan, A. Raja, A. Ram, M. Riedl, S. Russell, A. Sabharwal, J-G Smaus, G. Sukthankar, K. Tuyls, R. van der Meyden, A. Halevy, L. Mihalkova and S. Natarajan. Reports of the AAAI 2010 Conference Workshops, AI Magazine 31(4):95-108, 2010.

D. M. Gabbay and A. S. d'Avila Garcez. Logical Modes of Attack in Argumentation Networks. Studia Logica 93:199-230, 2009.

R. V. Borges, A. S. d'Avila Garcez and L. C. Lamb. A Neural-Symbolic Perspective on Analogy. Commentary on Leech et al, Analogy as Relational Priming, Behavioral and Brain Sciences, 31(4), Cambridge University Press, 2008.

P. Dafas and A. S. d'Avila Garcez. Discovering Meaningful Rules from Gene Expression Data. Current Bioinformatics, 2(3):157-168, Bentham Science, September 2007.

A. S. d'Avila Garcez, D. M. Gabbay, O. Ray and J. Woods. Abductive Reasoning in Neural-Symbolic Learning Systems. Topoi: An International Review of Philosophy, 26:37-49, Logic and Cognition, J. vanBenthem, W. Hodges and H. Hodges (eds.), Springer-Verlag, March 2007.

A. S. d'Avila Garcez, L. C. Lamb and D. M. Gabbay. Connectionist Modal Logic: Representing Modalities in Neural Networks. Theoretical Computer Science, 371(1-2):34-53, Elsevier, February 2007.

A. S. d'Avila Garcez, L. C. Lamb and D. M. Gabbay. Connectionist Computations of Intuitionistic Reasoning. Theoretical Computer Science, 358(1):34-55, Elsevier, July 2006.

A. S. d'Avila Garcez and L. C. Lamb. A Connectionist Computational Model for Epistemic and Temporal Reasoning. Neural Computation 18(7):1711-1738, MIT Press, July 2006.

A. S. d'Avila Garcez, D. M. Gabbay and L. C. Lamb. Value-based Argumentation Frameworks as Neural-Symbolic Learning Systems. Journal of Logic and Computation 15(6):1041-1058, Oxford University Press. 2005.

A. S. d'Avila Garcez, D. M. Gabbay, S. Holldobler and J. G. Taylor (eds). Journal of Applied Logic, Special Volume on Neural-Symbolic Systems (editorial), Elsevier, 2004.

A. S. d'Avila Garcez, L. C. Lamb, K. Broda and D. M. Gabbay. Applying Connectionist Modal Logics to Distributed Knowledge Representation Problems, International Journal on Artificial Intelligence Tools, 2004.

A. S. d'Avila Garcez, A. Russo, B. Nuseibeh and J. Kramer. Combining Abductive Reasoning and Inductive Learning to Evolve Requirements Specifications. IEE Proceedings - Software 150(1):25-38, 2003.

A. S. d'Avila Garcez and C. E. Thomaz. Book Review: Neural Networks for Pattern Recognition, by Christopher M. Bishop, Oxford University Press, Journal of Logic and Computation 13(4), 2003.

A. S. d'Avila Garcez, K. Broda and D. M. Gabbay. Symbolic Knowledge Extraction from Trained Neural Networks: A Sound Approach. Artificial Intelligence, 125(1-2):153-205, January 2001.

A. S. d'Avila Garcez and G. Zaverucha. The Connectionist Inductive Learning and Logic Programming System. Applied Intelligence Journal, Special Issue on Neural Networks and Structured Knowledge, 11(1):59-77, 1999.

Contributions to Books

Joe Townsend, Esma Mansouri-Benssassi, Kwun Ho Ngan, Artur d’Avila Garcez. Discovery of Visual Concepts from Convolutional Neural Networks. In Compendium of Neuro-Symbolic Artificial Intelligence, Pascal Hitzler, Md Kamruzzaman Sarker and Aaron Eberhart (eds.), IOS Press, 2023.

Luciano Serafini, Artur d’Avila Garcez, Samy Badreddine, Federico Bianchi, Ivan Donadello and Michael Spranger. Logic Tensor Networks: Theory and Applications. In Neuro-Symbolic Artificial Intelligence: The State of the Art, Pascal Hitzler and Md Kamruzzaman Sarker (eds.), IOS Press, May 2022.

T. R. Besold, A. S. d'Avila Garcez, S. Bader, H. Bowman, P. Domingos, P. Hitzler, K.-U. Kuehnberger, L. C. Lamb, D. Lowd, P. M. V. Lima, L. de Penning, G. Pinkas, H. Poon, G. Zaverucha. Neural-Symbolic Learning and Reasoning: A Survey and Interpretation. In Neuro-Symbolic Artificial Intelligence: The State of the Art, Pascal Hitzler and Md Kamruzzaman Sarker (eds.), IOS Press, May 2022.

A. S. d'Avila Garcez and L. C. Lamb. Learning and Argumentation in Neural-Symbolic Computation. In Norbert M. Seel (ed.), Encyclopedia of the Sciences of Learning, Springer, 2011.

A. S. d'Avila Garcez and L. C. Lamb. Cognitive Reasoning and Knowledge Representation. In V. Cutsuridis, A. Hussain and J. G. Taylor (eds.) Perception-Action Cycle: Models, Algorithms and Hardware, Springer, 2011.

A. S. d'Avila Garcez. Advances in Neural-Symbolic Learning Systems: Modal and Temporal Reasoning. In Perspectives of Neural-Symbolic Integration, B. Hammer and P. Hitzler (eds.), Springer. 2007.

A. S. d'Avila Garcez and L. C. Lamb. Neural-Symbolic Systems and The Case for Non-Classical Reasoning. In We Will Show Them: Essays in Honour of Dov Gabbay, Vol.1, S. N. Artemov, H. Barringer, A. S. d'Avila Garcez, L. C. Lamb and J. Woods (eds.), International Federation for Computational Logic, College Publications. 2005.

A. S. d'Avila Garcez. On Gabbay's Fibring Methodology for Bayesian and Neural Networks. In D. A. Gillies (ed.), Laws and Models in Science, King's College Publications, 2004.

A. S. d'Avila Garcez, L. C. Lamb and D. M. Gabbay. Neural-Symbolic Intuitionistic Reasoning. In Frontiers in Artificial Intelligence and Applications, A. Abraham, M. Koppen and K. Franke (eds.), Proceedings of the Third International Conference on Hybrid Intelligent Systems (HIS'03), IOS Press, Melbourne, Australia, ISBN 1-58603-3948, December 2003.

A. S. d'Avila Garcez, G. Zaverucha and L. A. V. de Carvalho. Logic Programming and Inductive Learning in Artificial Neural Networks (revised version). In C. Herrman, F. Reine and A. Strohmaier, (eds.), Knowledge Representation in Neural Networks, pages 33-46, Logos-Verlag, Berlin, ISBN 3-931216-77-2, 1997.

Conferences and Workshops

J. P. G. de Souza, A. S. d'Avila Garcez, G. Zaverucha. Hypergraph Neural Networks with Logic Clauses. IEEE World Congress on Computational Intelligence (IEEE WCCI IJCNN 2024), Yokohama, Japan, 30 June - 5 July 2024.

K. H. Ngan, J. Phelan, S. Sadeghi-Afgeh, J. Townsend, A. S. d'Avila Garcez. Symbolic Knowledge Extraction and Distillation into Convolutional Neural Networks to Improve Medical Image Classification. IEEE World Congress on Computational Intelligence (IEEE WCCI IJCNN 2024), Yokohama, Japan, 30 June - 5 July 2024.

Q. Su, C. Kloukinas, A. S. d'Avila Garcez. Interpretable Neural Networks for Time Series Forecasting through Modularity and Feature Selection using Attention. IEEE World Congress on Computational Intelligence (IEEE WCCI IJCNN 2024), Yokohama, Japan, 30 June - 5 July 2024.

Kwun Ho Ngan, James Phelan, Esma Mansouri-Benssassi, Joe Townsend and Artur d'Avila Garcez. Closing the Neural-Symbolic Cycle: Knowledge Extraction, User Intervention and Distillation from Convolutional Neural Networks. 17th International Workshop on Neural-Symbolic Learning and Reasoning, NeSy2023, La Certosa di Pontignano, Siena, Italy, July 2023.

Sofoklis Kyriakopoulos and Artur d'Avila Garcez. Continual Reasoning: Non-monotonic Reasoning in Neurosymbolic AI using Continual Learning. 17th International Workshop on Neural-Symbolic Learning and Reasoning, NeSy2023, La Certosa di Pontignano, Siena, Italy, July 2023.

S. Tran, A. S. d'Avila Garcez. Neurosymbolic Reasoning and Learning with Restricted Boltzmann Machines. Thirty-Seventh AAAI Conference on Artificial Intelligence, AAAI 2023, Washington DC, USA, Feb 2023.

H. Stromfelt, L. Dickens, A. d'Avila Garcez, A. Russo. Formalizing Coherence and Consistency Applied to Transfer Learning in Neuro-Symbolic Autoencoders. NeurIPS 2022, New Orleans, LA, Dec 2022.

K. Ngan, A. d’Avila Garcez, J. Townsend. Extracting Meaningful High-Fidelity Knowledge from Convolutional Neural Networks. IEEE WCCI 2022, IJCNN, Padua, Italy, July 2022.

Benedikt Wagner and Artur S. d'Avila Garcez. Neural-Symbolic Integration for Interactive Learning and Conceptual Grounding. Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS 2021), Workshop on Human and Machine Decisions, Virtual, December 2021.
Harald Stroemfelt, Luke Dickens, Artur d'Avila Garcez and Alessandra Russo. Coherent and Consistent Relational Transfer Learning with Autoencoders. In Proceedings of 15th International Workshop on Neural-Symbolic Learning and Reasoning (NeSy'21), 1st International Joint Conference on Learning and Reasoning (IJCLR), Virtual, 25-27 October 2021.
Benedikt Wagner and Artur S. d'Avila Garcez, Neural-Symbolic Integration for Fairness in AI, AAAI 2021 Spring Symposium on Combining Machine Learning and Knowledge Engineering (AAAI-MAKE 2021), Stanford University, Palo Alto, CA, USA, March 22-24, 2021.
Christian Percy, Artur d'Avila Garcez, Simo Dragicevic and Sanjoy Sarkar. Lessons Learned from Problem Gambling Classification: Indirect Discrimination and Algorithmic Fairness. In Proceedings of AAAI Fall Symposium, AI for Social Good, Arlington, Virginia, USA, November 2020.
Henrique Lemos, Pedro Avelar, Marcelo Prates, Luis Lamb, Artur d'Avila Garcez. Neural-Symbolic Relational Reasoning on Graph Models: Effective Link Inference and Computation from Knowledge Bases. 29th International Conference on Artificial Neural Networks (ICANN 2020), Bratislava, Slovakia, Springer LNCS, September 2020.
Regis Riveret, Son Tran and Artur d'Avila Garcez. Neuro-Symbolic Probabilistic Argumentation Machines. In Proc. 17th International Conference on Principles of Knowledge Representation and Reasoning (KR2020), Rhodes, Greece, September 2020.
Kwun Ho Ngan, Artur d'Avila Garcez, Karen M. Knapp, Andy Appelboam, Constantino Carlos Reyes-Aldasoro. A Machine Learning Approach for Colles Fracture Treatment Diagnosis. In Proceedings of the 24th UK Conference on Medical Image Understanding and Analysis (MIUA'2020), University of Oxford, Oxford, UK, July 2020.
Luis C. Lamb, Artur d'Avila Garcez, Marco Gori, Marcelo O.R. Prates, Pedro H.C. Avelar and Moshe Y. Vardi. Graph Neural Networks Meet Neural-Symbolic Computing: A Survey and Perspective. In Proc. IJCAI 2020, Yokohama, Japan, July 2020.
C. Charitou, A. d'Avila Garcez and S. Dragicevic. Semi-supervised GANs for Fraud Detection. In Proc. IEEE International Joint Conference on Neural Networks, IJCNN 2020, Glasgow, UK, July 2020.
A. White and A. d'Avila Garcez. Measurable Counterfactual Local Explanations for Any Classifier. In Proc. 24th European Conference on Artificial Intelligence (ECAI 2020), Santiago de Compostela, Spain, June 8-12, 2020.
D. Philps, T. Weyde and A. d'Avila Garcez. Making Good on LSTMs Unfulfilled Promise. Thirty-third Conference on Neural Information Processing Systems (NeurIPS 2019), Workshop on Robust AI in Financial Services: Data, Fairness, Explainability, Trustworthiness, and Privacy, Vancouver, Canada, December 2019.
S. Odense and A. d'Avila Garcez. Layerwise Knowledge Extraction from Deep Convolutional Networks. Thirty-third Conference on Neural Information Processing Systems (NeurIPS 2019), Knowledge Representation and Reasoning Meets Machine Learning Workshop, Vancouver, Canada, December 2019.
S. Dragicevic, A. d'Avila Garcez, C. Percy and S. Sarkar. Understanding the Risk Profile of Gambling Behaviour through Machine Learning Predictive Modelling and Explanation. Thirty-third Conference on Neural Information Processing Systems (NeurIPS 2019), Knowledge Representation and Reasoning Meets Machine Learning Workshop, Vancouver, Canada, December 2019.
D Philps, T. Weyde, A. d'Avila Garcez and R. Batchelor. Investment Decision with Continuous Learning based on Memory-Augmented Neural Networks. In Proc. NIPS 2018 Workshop on Challenges and Opportunities for AI in Financial Services: the Impact of Fairness, Explainability, Accuracy, and Privacy. Workshop at NIPS'18, Montreal, Canada, December 2018.
A. d'Avila Garcez, M. Gori, L. Lamb, L. Serafini, M. Spranger, S. Tran. Neural-Symbolic Computing: An Effective Methodology for Principled Integration of Machine Learning and Reasoning. In 13th International Workshop on Neural-Symbolic Learning and Reasoning (NeSy18), Human-Level AI Conference, Prague, Czech Republic, Aug 2018.
A. S. d'Avila Garcez, Neural-Symbolic Systems for Human-Like Computing (Abstract). In Human-Like Neural-Symbolic Computing (Dagstuhl Seminar 17192), Dagstuhl reports, Schloss Dagstuhl, Leibniz-Zentrum fuer Informatik, Germany, 2017.
L. Bechberger, A. S. d'Avila Garcez, R. Garrido Alhama, M. Gori, L. Serafini, M. Spranger and T. Weyde. Logic Tensor Networks Hackathon (Abstract). In Human-Like Neural-Symbolic Computing (Dagstuhl Seminar 17192), Dagstuhl reports, Schloss Dagstuhl, Leibniz-Zentrum fuer Informatik, Germany, 2017.
S. Cherla, S. Tran, A. S. d'Avila Garcez and T. Weyde. Generalising the Discriminative Restricted Boltzmann Machines. In Proc. 26th International Conference on Artificial Neural Networks, ICANN 2017, Alghero, Sardinia, Italy, September 2017.
S. Odense and A. S. d'Avila Garcez. Extracting M of N Rules from Restricted Boltzmann Machines. In Proc. 26th International Conference on Artificial Neural Networks, ICANN 2017, Alghero, Sardinia, Italy, September 2017.
I. Donadello, L. Serafini and A. S. d'Avila Garcez. Logic Tensor Networks for Semantic Image Interpretation. In Proceedings of 26th International Joint Conference on Artificial Intelligence (IJCAI 2017), Melbourne, Australia, August 2017.
A. J. Russell, E. Benetos and A. S. d'Avila Garcez. On the Memory Properties of Recurrent Neural Models. In Proceedings of IEEE International Joint Conference on Neural Networks (IJCNN 2017), Anchorage, Alaska, USA, May 2017.
L. Serafini, I. Donadello and A. S. d'Avila Garcez. Learning and Reasoning in Logic Tensor Networks: Theory and Application to Semantic Image Interpretation. In 32nd ACM Symposium on Applied Computing, SAC 2017, Marrakesh, Morocco, April 2017.
S. Sarkar, T. Weyde, A. S. d'Avila Garcez, G. Slabaugh, S. Dragicevic and C. Percy. Accuracy and Interpretability Trade-offs in Machine Learning Applied to Safer Gambling. Cognitive Computation: Integrating Neural and Symbolic Approaches, Workshop at NIPS'16, Barcelona, Spain, December 2016.
A. S. d'Avila Garcez and L. Serafini. Logic Tensor Networks (extended abstract). Machine Intelligence 20: Human-like Computing, Cumberland Lodge, Windsor, UK, October 2016.
L. Serafini and A. S. d'Avila Garcez. Learning and Reasoning with Logic Tensor Networks. In Proc. 15th International Conference of the Italian Association for Artificial Intelligence (AI*IA'16), Genoa, Italy, November 2016.
C. Percy, A. S. d'Avila Garcez, S. Dragicevic, M. Franca, G. Slabaugh and T. Weyde. The Need for Knowledge Extraction: Understanding Harmful Gambling Behavior with Neural Networks, In Proceedings of 22nd European Conference on Artificial Intelligence (ECAI 2016), The Hague, Netherlands, September 2016.
L. Serafini and A. S. d'Avila Garcez. Logic Tensor Networks: Deep Learning and Logical Reasoning from Data and Knowledge. 11th International Workshop on Neural-Symbolic Learning and Reasoning (NeSy16), The New School, New York, July 2016. ArXiv preprint arXiv:1606.04422.
O. Yilmaz, A. S. d'Avila Garcez and D. Silver. A Proposal for Common Dataset in Neural-Symbolic Reasoning Studies. 11th International Workshop on Neural-Symbolic Learning and Reasoning (NeSy16), The New School, New York, July 2016.
S. Tran and A. S. d'Avila Garcez. Adaptive Transferred-profile Likelihood Learning. In Proceedings of IEEE World Congress on Computational Intelligence, International Joint Conference on Neural Networks (IJCNN 2016), Vancouver, Canada, July 2016.
M. Franca, A. S. d'Avila Garcez and G. Zaverucha. Relational Knowledge Extraction from Neural Networks. Cognitive Computation: Integrating Neural and Symbolic Approaches, Workshop at NIPS 2015, Montreal, Canada, December 2015.
S. Cherla, S. Tran, T. Weyde and A. S. d'Avila Garcez. Hybrid Dynamic Melody Models. In Proceedings of 16th International Society for Music Information Retrieval Conference, ISMIR 2015, Malaga, Spain, October 2015.
A. Perotti, G. Boella and A. S. d'Avila Garcez, Runtime Verification Through Forward Chaining. In Proceedings of the 15th International Conference on Runtime Verification (RV'15), Springer LNCS, Vienna, Austria, September 2015.
T. Besold, K-U. Kuehnberger, A. S. d'Avila Garcez, A. Saffiotti, M. Fischer and A. Bundy. Anchoring Knowledge in Interaction: Towards a harmonic subsymbolic-symbolic framework and architecture of computational cognition. Eighth Conference on Artificial General Intelligence, Springer LNCS-LNAI, Berlin, Germany, July 2015.
A. Perotti, A. S. d'Avila Garcez and Guido Boella. Neural-Symbolic Monitoring and Adaptation. In Proceedings of The IEEE/INNS International Joint Conference on Neural Networks (IJCNN 2015), Killarney, Ireland, July 2015.
S. Cherla, S. Tran, A. S. d'Avila Garcez and T. Weyde. Discriminative Learning and Inference in the Recurrent Temporal RBM for Melody Modelling. In Proceedings of The IEEE/INNS International Joint Conference on Neural Networks (IJCNN 2015), Killarney, Ireland, July 2015.
S. Tran and A. S. d'Avila Garcez. Efficient Representation Ranking for Transfer Learning. In Proceedings of The IEEE/INNS International Joint Conference on Neural Networks (IJCNN 2015), Killarney, Ireland, July 2015.
S. Sigtia, E. Benetos, T. Weyde, A. S. d'Avila Garcez, N. Boulanger-Lewandowski and S. Dixon. A Hybrid Recurrent Neural Network for Music Transcription. 40th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP'15), Brisbane, Australia, April 2015.
A. S. d'Avila Garcez, L. de Raedt, L. C. Lamb, R. Miikkulainen, P. Hitzler, T. Icard, T. Besold, P. Foldiak, D. Silver and K.U. Kuehnberger. Neural-Symbolic Learning and Reasoning: Contributions and Challenges, AAAI Spring Symposium on Knowledge Representation and Reasoning: Integrating Symbolic and Neural Approaches, Stanford University, CA, March 2015.
M. Franca, A. S. d'Avila Garcez and G. Zaverucha, Neural Relational Learning through Semi-Propositionalization of Bottom Clauses, AAAI Spring Symposium on Knowledge Representation and Reasoning: Integrating Symbolic and Neural Approaches, Stanford University, CA, March 2015.
S. Guo, A. Roudsari and A. S. d'Avila Garcez. Modelling clinical diagnostic errors: A system dynamics approach. Information Technology and Communications in Health (ITCH'2015), Victoria, BC, Canada, February-March, 2015.
H. Ali, S. Tran, A. S. d'Avila Garcez and T. Weyde. Towards Deep Learning from Audio Big Data (Abstract). 1st UCL Workshop on the Theory of Big Data, University College London, UK, January 2015.
A. S. d'Avila Garcez, Neural-Symbolic Computing, Deep Logic Networks and Applications (Abstract). In Neural-Symbolic Learning and Reasoning (Dagstuhl Seminar 14381), Dagstuhl reports, Schloss Dagstuhl, Leibniz-Zentrum fuer Informatik, Germany, 2014.
S. Tran and A. S. d'Avila Garcez. Low-cost Representation for Restricted Boltzmann Machines. In Proceedings of 21st International Conference on Neural Information Processing (ICONIP'14), Kuching, Malaysia, Lecture Notes in Computer Science LNCS, Springer, November 2014.
S. Cherla, T. Weyde and A. S. d'Avila Garcez, Multiple Viewpiont Melodic Prediction with Fixed-Context Neural Networks. In Proceedings of 15th International Society for Music Information Retrieval Conference, ISMIR 2014, Taipei, Taiwan, October 2014.
S. Sigtia, E. Benetos, S. Cherla, T. Weyde, A. S. d'Avila Garcez and S. Dixon, RNN-based Music Language Models for Improving Automatic Music Transcription. In Proceedings of 15th International Society for Music Information Retrieval Conference, ISMIR 2014, Taipei, Taiwan, October 2014.
S. Guo, A. Roudsari and A. S. d'Avila Garcez. A Causal Loop Approach to the Study of Diagnostic Errors. In Proc. of 25th European Medical Informatics Conference (MIE2014), Istanbul, Turkey, August 2014.
A. Perotti, Guido Boella and A. S. d'Avila Garcez, Runtime Verification Through Forward Chaining (extended abstract), In Workshop on Horn Clauses for Verification and Synthesis (HCVS), 26th International Conference on Computer Aided Verification (CAV), Vienna Summer of Logic, Vienna, Austria, July 2014. Electronic Proceedings in Theoretical Computer Science (EPTCS).
A. Perotti, A. S. d'Avila Garcez and Guido Boella, Neural Networks for Runtime Verification. The 2014 International Joint Conference on Neural Networks (IJCNN 2014), IEEE WCCI, Beijing, China, July 2014.
S. Tran, E. Benetos and A. S. d'Avila Garcez, Learning Motion-Difference Features using Gaussian Restricted Boltzmann Machines for Efficient Human Action Recognition. The 2014 International Joint Conference on Neural Networks (IJCNN 2014), IEEE WCCI, Beijing, China, July 2014.
L. de Penning, A. S. d'Avila Garcez, L. Lamb, A. Stuiver and J. J. Meyer, Applying Neural-Symbolic Cognitive Agents in Intelligent Transport Systems to reduce CO2 emissions. The 2014 International Joint Conference on Neural Networks (IJCNN 2014), IEEE WCCI, Beijing, China, July 2014.
A. Perotti, Guido Boella and A. S. d'Avila Garcez. Monitoring and Learning in Multiagent Systems. 17th International Workshop on Coordination, Organisations, Institutions and Norms (COIN 2014), Paris, France, May 2014.
L. de Penning, A. S. d'Avila Garcez, L. C. Lamb and J. J. Meyer. Neural-Symbolic Cognitive Agents: Theory, Architecture and Application. In Proceedings of 13th International Conference on Autonomous Agents and Multiagent Systems, AAMAS'14, Paris, France, May 2014.
H. Ali, A. S. d'Avila Garcez, S. Tran and X. Zhou, Hybrid Features Combination for Audio Data Classification. Machine Learning and Data Analytics Symposium, Doha, Qatar, March 2014.
S. Tran, D. Wolff, T. Weyde and A. S. d'Avila Garcez. Feature Preprocessing with Restricted Boltzmann Machines for Music Similarity Learning. In Proceedings of the Audio Engineering Society 53rd International Conference on Semantic Audio, London, UK, January 2014. (winner of the prize for fully-reproducible work)
S. Tran and A. S. d'Avila Garcez. Adaptive Feature Ranking for Unsupervised Transfer Learning. ArXiv:1312.6190, Cornell University, http://arxiv.org/abs/1312.6190, December 2013.
M. Franca, A. S. d'Avila Garcez and G. Zaverucha. Relational Knowledge Extraction using Attribute-Value Learners. Imperial College Computing Student Workshop, ICCSW 2013, Schloss Dagstuhl OpenAccess Series in Informatics, OASIcs, London, UK, September 2013.
L. de Penning, A. S. d'Avila Garcez and J. J. Meyer. Dreaming Machines: On multimodal fusion and information retrieval using neural-symbolic cognitive agents. Imperial College Computing Student Workshop, ICCSW 2013, Schloss Dagstuhl OpenAccess Series in Informatics, OASIcs, London, UK, September 2013.
S. Cherla, T. Weyde, A. S. d'Avila Garcez and M. Pearce. A Distributed Model for Multiple-Viewpoint Melodic Prediction. In Proceedings of 14th International Society for Music Information Retrieval Conference, ISMIR 2013, Curitiba, Brazil, November 2013. (winner of best student paper award)
S. Cherla, A. S. d'Avila Garcez and T. Weyde. A Neural Probabilistic Model for Predicting Melodic Sequences. In ECML Workshop on Machine Learning and Music, MML 2013, Prague, Czech Republic, September 2013.
S. Tran and A. S. d'Avila Garcez. Knowledge Extraction from Deep Belief Networks for Images. In Proceedings of IJCAI Workshop on Neural-Symbolic Learning and Reasoning, NeSy13, Beijing, China, August 2013.
A. Perotti, G. Boella and A. S. d'Avila Garcez. Combining Runtime Verification and Property Adaptation through Neural-Symbolic Integration. In Proceedings of IJCAI Workshop on Neural-Symbolic Learning and Reasoning, NeSy13, Beijing, China, August 2013.
A. Perotti, G. Boella and A. S. d'Avila Garcez. Combining Runtime Verification and Property Adaptation through Neural-Symbolic Integration (extended abstract). In Computability in Europe 2013: The Nature of Computation, Milan, Italy, LNCS, July 2013.
M. Franca, G. Zaverucha and A. S. d'Avila Garcez. Fast Relational Learning using Bottom Clauses in Artificial Neural Networks. In 22nd International Conference on Inductive Logic Programming, ILP 2012, Dubrovnik, Croatia, September 2012.
S. Tran and A. S. d'Avila Garcez. Logic Extraction from Deep Belief Networks. In Proceedings of ICML Workshop on Representation Learning, Edinburgh, Scotland, July 2012.
A. Perotti, G. Boella, A. d'Avila Garcez and D. Rispoli. Neural-Symbolic Rule-Based Monitoring. In Proceedings of AAAI Workshop on Neural-Symbolic Learning and Reasoning NeSy12, Toronto, Canada, July 2012.
L. de Penning, R. den Hollander, H. Bouma, G. Burghouts and A. S. d'Avila Garcez. A Neural-Symbolic Cognitive Agent with a Minds Eye. In Proceedings of AAAI Workshop on Neural-Symbolic Learning and Reasoning NeSy12, Toronto, Canada, July 2012.
A. S. d'Avila Garcez and G. Zaverucha. Multi-instance Learning using Recurrent Neural Networks. In Proceedings of International Joint Conference on Neural Networks, IJCNN 2012, Brisbane, Australia, June 2012.

G. Boella, S. Colombo-Tosatto, A. S. d'Avila Garcez, V. Genovese, A. Perotti and L. van der Torre. Learning and Reasoning about Norms using Neural-Symbolic Systems. In Proceedings of 11th International Conference on Autonomous Agents and Multiagent Systems, AAMAS'12, Valencia, Spain, June 2012.

A. Perotti, G. Boella and A. S. d'Avila Garcez. A Neural-Symbolic Approach to the Contemporary Theory of Metaphor. In NIPS workshop on Philosophy and Machine Learning, Sierra Nevada, Spain, December 2011.

L. de Penning, A. S. d'Avila Garcez, L. C. Lamb and J. J. Meyer. Neural-Symbolic Cognitive Agents: Architecture and Theory. In Proceedings of Imperial College Computing Student Workshop ICCSW'11, London, UK, September 2011.

L. de Penning, A. S. d'Avila Garcez, L. C. Lamb and J. J. Meyer. A Neural-Symbolic Cognitive Agent for Online Learning and Reasoning. In Proceedings of 22nd International Joint Conference on Artificial Intelligence, IJCAI'11, Barcelona, Spain, July 2011.

R. V. Borges, A. S. d'Avila Garcez, L. C. Lamb and B. Nuseibeh. Learning to Adapt Requirements Specifications of Evolving Systems. In Proceedings of 33rd ACM/IEEE International Conference on Software Engineering, ICSE'11, New Ideas and Emerging Results track, Waikiki, Hawaii, May 2011.

G. Boella, S. Colombo Tosatto, A. S. d'Avila Garcez, V. Genovese, D. Ienco and L. van der Torre. A Neural-Symbolic System for Normative Agents. In Proceedings of 10th International Conference on Autonomous Agents and Multiagent Systems AAMAS'11, Taipei, Taiwan, May 2011.

A. S. d'Avila Garcez. Neurons and Symbols: A Manifesto. In Dagstuhl Seminar Proceedings 10302. Learning paradigms in dynamic environments, B. Hammer, P. Hitzler, W. Maass and M. Toussaint (eds.), Schloss Dagstuhl, Leibniz-Zentrum fuer Informatik, Germany, 2010.

E. Komendantskaya, K. Broda and A. S. d'Avila Garcez. Neuro-Symbolic Representation of Logic Programs Defining Infinite Sets. In Proceedings of 20th International Conference on Artificial Neural Networks ICANN 2010, Thessaloniki, Greece, September 2010.

R. V. Borges, A. S. d'Avila Garcez and L. C. Lamb. Representing, Learning and Extracting Temporal Knowledge from Neural Networks: A Case Study. In Proceedings of 20th International Conference on Artificial Neural Networks ICANN 2010, Thessaloniki, Greece, September 2010.

R. V. Borges, A. S. d'Avila Garcez and L. C. Lamb. Integrating Model Verification and Self-Adaptation. In Proceedings of 25th IEEE/ACM International Conference on Automated Software Engineering ASE'10, Antwerp, Belgium, September 2010.

L. de Penning, A. S. d'Avila Garcez, L. C. Lamb and J. J. Meyer. An Integrated Neural Symbolic Cognitive Agent Architecture for Training and Assessment in Simulators. In AAAI Workshop on Neural-Symbolic Learning and Reasoning NeSy'10, Atlanta, Georgia, USA, July 2010.

N. Ryman-Tubb and A. S. d'Avila Garcez. SOAR: Sparse Oracle-based Adaptive Rule Extraction: Knowledge Extraction from Large-Scale Datasets to Detect Credit Card Fraud. In 23rd International Joint Conference on Neural Networks IJCNN 2010, Barcelona, Spain, July 2010.

M. Guillame-Bert, K. Broda and A. S. d'Avila Garcez. First-Order Logic Learning using Neural Networks. In 23rd International Joint Conference on Neural Networks IJCNN 2010, Barcelona, Spain, July 2010.

E. Komendantskaya, K. Broda and A. S. d'Avila Garcez. Using Inductive Types for Ensuring Correctness of Neuro-Symbolic Computations. Computability in Europe CiE 2010, Ponta Delgada, Portugal, June 2010.

G. Boella, S. Colombo Tosatto, A. S. d'Avila Garcez and V. Genovese. On the Relationship between I-O Logic and Connectionism. In Nonmonotonic Reasoning NMR 2010 Preferences and Norms Workshop, Toronto, Canada, May 2010.

Lu Ren and A. S. d'Avila Garcez. Symbolic Knowledge Extraction from Support Vector Machines: A Geometric Approach. In Proceedings of 15th International Conference on Neural Information Processing (ICONIP'08), Auckland, New Zealand, Lecture Notes in Computer Science LNCS, Springer, November 2008.

R. V. Borges, L. C. Lamb and A. S. d'Avila Garcez. Reasoning and Learning about Past Temporal Knowledge in Connectionist Models. In Proceedings of the 20th International Joint Conference on Neural Networks IJCNN 2007, Orlando, USA, August 2007.

C. Child, K. Stathis and A. S. d'Avila Garcez. Learning to Act with RVRL Agents. In 14th RCRA Workshop, Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion, Rome, Italy, July 2007.

L. C. Lamb, R. V. Borges and A. S. d'Avila Garcez. A Connectionist Cognitive Model for Temporal Synchronisation and Learning. In Proceedings of the 22nd National Conference on Artificial Intelligence AAAI 2007, Vancouver, Canada, July 2007.

R. V. Borges, L. C. Lamb and A. S. d'Avila Garcez. Towards Reasoning about the Past in Neural-Symbolic Systems. Proceedings of IJCAI Workshop on Neural-Symbolic Learning and Reasoning NeSy07, Hyderabad, India, January 2007.

R. V. Borges, L. C. Lamb and A. S. d'Avila Garcez. Combining Architectures for Temporal Learning in Neural-Symbolic Systems. In Proceedings of 6th International Conference on Hybrid Intelligent Systems (HIS'06), IEEE Computer Society, December 2006.

R. Carneiro, S. S. Dias, D. Fardin Jr., H. Oliveira, A. S. d'Avila Garcez, A. F. de Souza. Improving VG-RAM Neural Network Performance using Knowledge Correlation. In Proceedings of 13th International Conference on Neural Information Processing (ICONIP'06), Hong Kong, Lecture Notes in Computer Science LNCS, Springer-Verlag, October 2006.

O. Ray and A. S. d'Avila Garcez. Towards the Integration of Abduction and Induction in Artificial Neural Networks. In Proceedings of ECAI Workshop on Neural-Symbolic Learning and Reasoning NeSy06, Riva del Garda, Italy, August 2006.

A. S. d'Avila Garcez, L. C. Lamb and D. M. Gabbay. A Connectionist Model for Constructive Modal Reasoning. In Advances in Neural Information Processing Systems 18, Proceedings of the NIPS 2005 Conference, Vancouver, Canada, Y. Weiss, B. Scholkopf and J. Platt (eds.), MIT Press, 2006.

P. Hitzler, S. Bader and A. S. d'Avila Garcez. Ontology Learning as a Use-Case for Neural-Symbolic Integration. In Proceedings of IJCAI Workshop on Neural-Symbolic Learning and Reasoning NeSy05, Edinburgh, Scotland, August 2005.

A. S. d'Avila Garcez. Fewer Epistemological Challenges for Connectionism. In Proceedings of Computability in Europe 2005: New Computational Paradigms, Amsterdam, Holland, Lecture Notes in Computer Science LNCS, Springer-Verlag, June 2005.

S. Bader, A. S. d'Avila Garcez and P. Hitzler. Computing First Order Logic Programs by Fibring Artificial Neural Networks. In Proceedings of 18th International FLAIRS Conference, AAAI Press, Florida, USA, May 2005.

A. S. d'Avila Garcez, D. M. Gabbay and L. C. Lamb. Argumentation Neural Networks. In Proceedings of 11th International Conference on Neural Information Processing (ICONIP'04), Calcutta, India, Lecture Notes in Computer Science LNCS, Springer-Verlag, November 2004.

O. Rodrigues, A. S. d'Avila Garcez and A. Russo. Reasoning about Requirements Evolution using Clustered Belief Revision (revised version). In Proceedings of the Brazilian Symposium on Artificial Intelligence (SBIA'04), Sao Luis, Brazil, Lecture Notes in Artificial Intelligence LNAI, Springer-Verlag, October 2004.

A. S. d'Avila Garcez, D. M. Gabbay and L. C. Lamb. Towards a Connectionist Argumentation Framework. In Proceedings of 16th European Conference on Artificial Intelligence ECAI 2004, Valencia, Spain, IOS Press, August 2004.

A. S. d'Avila Garcez and D. M. Gabbay. Fibring Neural Networks. In Proceedings of 19th National Conference on Artificial Intelligence AAAI 2004. San Jose, California, USA, AAAI Press, July 2004.

A. S. d'Avila Garcez and L. C. Lamb. Reasoning about Time and Knowledge in Neural-Symbolic Learning Systems. In Advances in Neural Information Processing Systems 16, Proceedings of the NIPS 2003 Conference, Vancouver, Canada, S. Thrun, L. Saul and B. Schoelkopf (eds.), MIT Press, 2004.

O. Rodrigues, A. S. d'Avila Garcez and A. Russo. Reasoning about Requirements Evolution using Clustered Belief Revision, ESEC/FSE International Workshop on Intelligent Technologies for Software Engineering (WITSE'03), Helsinki, Finland, September 2003.

G. Spanoudakis, A. S. d'Avila Garcez and A. Zisman. Revising Rules to Capture Requirements Traceability Relations: A Machine Learning Approach, In Proceedings of 15th International Conference on Software Engineering and Knowledge Engineering (SEKE'03), San Francisco, USA, July 2003.

A. S. d'Avila Garcez, L. C. Lamb, K. Broda and D. M. Gabbay. Distributed Knowledge Representation in Neural-Symbolic Learning Systems: A Case Study, In Proceedings of 16th International FLAIRS Conference, AAAI Press, Florida, USA, May 2003.

A. S. d'Avila Garcez, L. C. Lamb and D. M. Gabbay. A Connectionist Inductive Learning System for Modal Logic Programming, In Proceedings of 9th IEEE International Conference on Neural Information Processing ICONIP'02, Singapore, November 2002.

A. S. d'Avila Garcez. Extended Theory Refinement in Knowledge-based Neural Networks. In Proceedings of IEEE International Joint Conference on Neural Networks IJCNN 2002, World Congress on Computational Intelligence, Honolulu, Hawaii, May 2002.

A. S. d'Avila Garcez, A. Russo, B. Nuseibeh and J. Kramer. An Analysis-Revision Cycle to Evolve Requirements Specifications. In Proceedings of the 16th IEEE International Conference on Automated Software Engineering (ASE-2001), San Diego, USA, November 2001.

A. S. d'Avila Garcez, K. Broda and D. M. Gabbay. Metalevel Priorities and Neural Networks. In Proceedings of the Workshop on the Foundations of Connectionist-Symbolic Integration ECAI2000, Berlin, Germany, August 2000.

A. S. d'Avila Garcez, K. Broda, D. M. Gabbay and A. F. de Souza. Knowledge Extraction from Trained Neural Networks: A Position Paper. In Proceedings of 6th IEEE International Conference on Neural Information Processing ICONIP'99, pages 685-691, Perth, Australia, November 1999.

R. Basilio, G. Zaverucha and A. S. d'Avila Garcez. Inducing Relational Concepts with Neural Networks via the LINUS System. In Proceedings of 5th International Conference on Neural Information Processing ICONIP'98, pages 1507-1510, Kitakyushu, Japan, October 1998.

A. S. d'Avila Garcez, G. Zaverucha and V. N. L. da Silva. Applying the Connectionist Inductive Learning and Logic Programming System to Power Systems Diagnosis. In Proceedings of the IEEE International Joint Conference on Neural Networks IJCNN 1997, pages 121-126, Houston, Texas, USA, June 1997.

A. S. d'Avila Garcez, G. Zaverucha and L. A. V. de Carvalho. Logic Programming and Inductive Learning in Artificial Neural Networks. In Proceedings of the Workshop on Knowledge Representation and Neural Networks, XX German Conference on Artificial Intelligence KI96, Dresden, Germany, pages 9-18, September 1996.

A. S. d'Avila Garcez, G. Zaverucha and L. A. V. de Carvalho. Logical Inference and Inductive Learning in Artificial Neural Networks. In Proceedings of the Workshop on Neural Networks and Structured Knowledge ECAI'96, pages 41-49, Budapest, Hungary, August 1996.

A. S. d'Avila Garcez, G. Zaverucha and V. N. L. da Silva. Programacao em Logica Estendida e Aprendizado Indutivo em Redes Neurais: Uma Aplicacao em Sistemas de Potencia. In Proceedings of the 3rd Simposio Brasileiro de Redes Neurais SBRN'96, Recife, Brazil, 1996. (In Portuguese)

A. S. d'Avila Garcez, G. Zaverucha and L. A. V. de Carvalho. Inferencia Logica e Aprendizado Automatico em Redes Neurais: Uma Representacao Integrada do Conhecimento. In Proceedings of the 2nd Congresso Brasileiro de Redes Neurais CBRN'95, Curitiba, Brazil, October 1995. (In Portuguese)

Journal Special Issues and Proceedings Edited

Artur S. d'Avila Garcez and Ernesto Jimenez-Ruiz (eds.), 16th International Workshop on Neural-Symbolic Learning and Reasoning, NeSy 2022, CEUR Workshop Proceedings, Sep 2022.
Alireza Tamaddoni-Nezhad, Alan Bundy, Artur d’Avila Garcez, Cesar Ferri, Nikos Katzouris, Stephen Muggleton, Ute Schmid (eds.), Special Volume on Learning and Reasoning, Machine Learning journal, Springer, 2022.
Fabio D'Asaro, Brian Caffo, Artur S. d'Avila Garcez, Emanuela Raffinetti (eds). Explainable AI in Healthcare and Finance. Frontiers in Artificial Intelligence, Lausanne, Switzerland, 2022.
Nikos Katzouris, Alexander Artikis, Luc De Raedt, Artur d'Avila Garcez, Ute Schmid, Sebastijan Dumancic, Jay Pujara (eds.), Special Volume on Learning and Reasoning, Machine Learning journal, Springer, 2021.
T. Besold, A. S. d'Avila Garcez (eds.), Neural-Symbolic Learning and Reasoning NeSy18, Special Volume of the Journal of Applied Logics, College Publications, London, 2019.
A. d'Avila Garcez, T. Besold, L. Bottou, R. Guha, K. Kersting, L. Lamb, G. Marcus and R. Miikkulainen (eds.), Deep Learning, Knowledge Representation and Reasoning. Special issue of the Journal of AI Research, 2018.
T. Besold, A. S. d'Avila Garcez, R. Guha and L. C. Lamb (eds.), Human-Like Neural-Symbolic Computing (Dagstuhl Seminar 17192), Dagstuhl reports, Schloss Dagstuhl, Leibniz-Zentrum fuer Informatik, Germany, 2017.
A. S. d'Avila Garcez, T. Besold, I. Noble (eds). Proceedings of the 12th International Workshop on Neural-Symbolic Learning and Reasoning NeSy17, London, UK, July 2017.
T. R. Besold, A. Bordes, A. d'Avila Garcez, G. Wayne (eds). Proceedings of the NIPS Workshop on Cognitive Computation: Integrating Neural and Symbolic Approaches (CoCo 2016), Barcelona, Spain, December 2016.
T, R. Besold, A. d'Avila Garcez, G. F. Marcus, R. Miikkulainen (eds). Proceedings of the NIPS Workshop on Cognitive Computation: Integrating Neural and Symbolic Approaches (CoCo 2015), Montreal, Canada, December 11-12, 2015. CEUR-WS-1584 (http://ceur-ws.org/Vol-1584/), 2016.
A. S. d'Avila Garcez, M. Gori, P. Hitzler and L. C. Lamb (eds.), Neural-Symbolic Learning and Reasoning (Dagstuhl Seminar 14381), Dagstuhl reports, Schloss Dagstuhl, Leibniz-Zentrum fuer Informatik, Germany, 2014.
T. R. Besold, A. S. d'Avila Garcez, K. U. Kuehnberger, T. C. Stewart (eds.), Biologically Inspired Cognitive Architectures, Special Volume on Neural-Symbolic Networks for Cognitive Capacities, Elsevier, 2014.
A. S. d'Avila Garcez, L. C. Lamb and P. Hitzler (eds). Proceedings of IJCAI International Workshop on Neural-Symbolic Learning and Reasoning NeSy13, Beijing, China, 2013.
A. S. d'Avila Garcez, L. C. Lamb and P. Hitzler (eds). Proceedings of AAAI International Workshop on Neural-Symbolic Learning and Reasoning NeSy12, Toronto, Canada, 2012.
A. S. d'Avila Garcez, L. C. Lamb and P. Hitzler (eds). Proceedings of IJCAI International Workshop on Neural-Symbolic Learning and Reasoning NeSy11, Barcelona, Spain, 2011.
K. Stathis, A. S. d'Avila Garcez and R. Givan (eds). Journal of Algorithms in Cognition, Informatics and Logic, Thematic Volume on Algorithmic Reinforcement Learning, Elsevier, 2009.

A. S. d'Avila Garcez and P. Hitzler (eds). Proceedings of IJCAI International Workshop on Neural-Symbolic Learning and Reasoning NeSy09, Pasadena, USA, July 2009.

A. S. d'Avila Garcez and P. Hitzler (eds). Proceedings of ECAI International Workshop on Neural-Symbolic Learning and Reasoning NeSy08, CEUR Proceedings Vol. 366, ISSN 1613-0073, Patras, Greece, 2008.

A. S. d'Avila Garcez, P. Hitzler and G. Tamburrini (eds). Proceedings of IJCAI International Workshop on Neural-Symbolic Learning and Reasoning NeSy07, CEUR Proceedings Vol. 230, ISSN 1613-0073, Hyderabad, India, 2007.

A. S. d'Avila Garcez, P. Hitzler and G. Tamburrini (eds). Proceedings of ECAI International Workshop on Neural-Symbolic Learning and Reasoning NeSy06, Trento, Italy, 2006.

A. S. d'Avila Garcez, J. Elman and P. Hitzler (eds). Proceedings of IJCAI International Workshop on Neural-Symbolic Learning and Reasoning NeSy05, Edinburgh, Scotland, 2005.

A. S. d'Avila Garcez, S. Dustdar, H. Gall, A. Lucia, A. Mana, T. Menzies, C. Rudolph, A. Russo (eds). Automated Software Engineering: Workshops at the 19th International Conference on Automated Software Engineering ASE'04. Austrian Computer Society (OCG), 2004.

A. S. d'Avila Garcez, D. M. Gabbay, S. Holldobler and J. G. Taylor (eds). Journal of Applied Logic, Volume 2(3), Special Volume on Neural-Symbolic Systems, Elsevier, September 2004.

A. S. d'Avila Garcez, G. Spanoudakis and A. Zisman (eds). Proceedings of ACM ESEC/FSE International Workshop on Intelligent Technologies for Software Engineering WITSE03, Helsinki, Finland, ISSN 1364-4009, 2003.

The electronic versions of the papers above are provided for personal use. Copyright is owned by the respective publishers and should be included in any distribution of the papers.