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Argente E, Boissier O, Carrascosa C, Fornara N, Mcburney P, Noriega P, Ricci A, Sabater-Mir J., Schumacher MIgnaz, Tampitsikas C et al..  2012.  Environment and Agreement Technologies. Proceedings of the First International Conference on Agreement Technologies. :260-261.
Argerlich J., Li CMin, Manyà F, Planes J.  2011.  Analyzing the Instances of the MaxSAT Evaluation. 14th International Conference on Theory and Applications of Satisfiability Testing, SAT 2011. 6695:360-361.
Argerlich J., Cabiscol A, Lynce I, Manyà F.  2009.  Sequential Encodings from Max-CSP into Partial Max-SAT. 12th International Conference on Theory and Applications of Satisfiability Testing (SAT 2009). LNCS 5584:161-166.
Argerlich J., Cabiscol A, Lynce I, Manyà F.  2008.  Modelling Max-CSP as Partial Max-SAT. 11th International Conference on Theory and Applications of Satisfiability Testing (SAT-2008). 4996:1-14.
Argerlich J., Li CMin, Manyà F, Planes J.  2008.  The First and Second Max-SAT Evaluations. Journal on Satisfiability, Boolean Modeling and Computation. 4:251-278.
Argerlich J., Cabiscol A, Lynce I, Manyà F.  2012.  Efficient Encodings from CSP into SAT, and from MaxCSP into MaxSAT. Multiple-Valued Logic and Soft Computing. 19:3-23.
Argerlich J., Domingo X, Li CMin, Manyà F, Planes J..  2006.  Towards Solving Many-Valued MaxSAT. Proceedings, 36th International Symposium on Multiple-Valued Logics (ISMVL-2006), Singapore.
Argerlich J., Manyà F.  2006.  Exact Max-SAT solvers for over-constrained problems. Journal of Heuristics. :375-392.
Argerlich J., Li CMin, Manyà F, Planes J.  2011.  Experimenting with the Instances of the MaxSAT Evaluation. 14th International Conference of the Catalan Association for Artificial Intelligence. 232:31-40.
Argerlich J., Manyà F.  2005.  Solving over-constrained problems with SAT technology. Lecture Notes in Computer Science. :1-15.
Argerlich J., Cabiscol A, Lynce I, Manyà F.  2010.  New Insights into Encodings from MaxCSP into Partial MaxSAT. 40th IEEE International Symposium on Multiple-Valued Logic (ISMVL). :46-52.
Argerlich J., Manyà F.  2008.  A Preprocessor for Max-SAT Solvers. 11th International Conference on Theory and Applications of Satisfiability Testing (SAT-2008). 4996:15-20.
Armengol E.  2007.  Usages of Generalization in CBR. Lecture Notes in Artificial Intelligence. :31-45.
Armengol E, Plaza E.  2005.  An ontological approach to represent molecular structure information. Lecture Notes in Computer Science. Lecture Notes in Bioinformatics. 3745:394-304.
Armengol E, Plaza E.  1995.  Integrating induction in a Case-based Reasoner. Lecture Notes in Artificial Intelligence. 984:3-17.
Armengol E.  2011.  Classification of Melanomas in situ using Knowledge Discovery with Explained CBR. Artificial Intelligence in Medicine. 51:12.
Armengol E, Plaza E.  2004.  Multiple-instance case-based learning for predictive toxicology. Lecture Notes in Computer Science. 3303:206-220.
Armengol E, Plaza E.  2005.  Using Symbolic Descriptions to Explain Similarity on CBR. Artificial intelligence research and development (CCIA-2005). :239-246.
Armengol E, García-Cerdaña A.  2012.  Refining Discretizations of Continuous-Valued Attributes. The 9th International Conference on Modeling Decisions for Artificial Intelligence. 7647:258-269.
Armengol E, Plaza E.  2003.  Remembering Similitude Terms in CBR. Machine Learning and Data Mining in Pattern Recognition (MLDM 2003). LNAI 2734:121-130.
Armengol E, Dellunde P, García-Cerdaña A.  2014.  Local and Global Similarities in Fuzzy Class Theory.. CCIA'14. 269:205-217.
Armengol E, Plaza E.  2000.  Bottom-up induction of feature terms. Machine Learning Journal. 41:259-294.
Armengol E, Dellunde P, García-Cerdaña A.  2015.  A Logical Study of Local and Global Graded Similarities. Applied Artificial Intelligence. 29:424-444.
Armengol E.  2008.  Building partial domain theories from explanations. Knowledge Intelligence. 2/08:19-24.
Armengol E, Dellunde P, García-Cerdaña A.  2012.  Towards a Fuzzy Extension of the López de Mántaras Distance. IPMU 2012. 297:81-90.
Armengol E, Plaza E.  2006.  Symbolic explanation of similarities in case-based reasoning. Computing and Informatics. 25:153-171.
Armengol E, Puyol-Gruart J.  2017.  A reward-based approach for preference modeling: A case study. Journal of Applied Logic. 23:51-69.
Armengol E, Dellunde P, Ratto C.  2011.  Lazy Learning Methods for Quality of Life Assessment in people with intellectual disabilities. CCIA-2011. :41-50.
Armengol E, Plaza E.  1995.  Explanation-based Learning: A Knowledge Level Analysis. AI Review. 9:19-35.
Armengol E, Plaza E.  2002.  Similarity of structured cases in CBR. Butlletí de L'ACIA. CCIA'2002. 5è Congrès Català d'Intel.ligència Artificial, Castelló, 24-25 d'Octubre del 2002.gs of the 5th Catalan Conference on Artificial Intelligence (CCIA'2002). :153-160.
Armengol E, Puertas E.  2006.  Learning from cooperation using justifications. Artificial Intelligence Research and Development. :47-54.
Armengol E, Palaudàries A., Plaza E.  2000.  Raonament basat en Casos per Pronosticar Riscos a Llarg Termini en Pacients amb Diabetis Mellitus. Proceedings of the. :209-218.
Armengol E, Plaza E.  2001.  Lazy Induction of Descriptions for Relational Case-Based Learning. Lecture Notes in Artificial Intelligence. 2167:13-24.
Armengol E, Dellunde P, García-Cerdaña A.  2010.  On Similarities in Fuzzy Description Logics. Logic, Algebra and Truth Degrees 2010. 502:44-49.
Armengol E, Puyol-Gruart J.  2015.  A Simple Experiment to Guide the Design of a Preference Model. Artificial Intelligence Research and Development, Proceedings of the 18th International Conference of the Catalan Association for Artificial Intelligence. 277:59-68.
Armengol E.  1998.  A Framework for Integrated Learning and Problem Solving.
Armengol E, Plaza E.  2003.  Relational Case-based Reasoning for Cancinogenic Activity Prediction. Artificial Intelligence Review. 20:121-141.
Armengol E, Puig S.  2011.  Combining two lazy learning methods for classification and knowledge discovery.. International Conference on Knowledge Discovery and Information Retrieval.
Armengol E, Plaza E.  2005.  Using Symbolic Similarity to Explain CBR in Classification Task. Fall Symposium. Proceedings AAAI. FS-05-04. :1-9.
Armengol E, Plaza E.  1994.  A Knowledge Level Model of Knowledge -Based Reasoning. Lecture Notes in Artificial Intelligence. 837:53-64.
Armengol E.  2009.  Using explanations for determining carcinogenecity in chemical compounds. International Journal on Engineering Applications of Artificial Intelligence. 22:8.
Armengol E, Puertas E.  2006.  Improving individual learning capabilities in Multi-Agent Systems. Workshop on Adaptation and Learning in autonomous agents and multi-agent systems. AAMAS-2006.
Armengol E, Torra V.  2015.  Generalization-Based k-Anonymization. 5861:207-218.
Armengol E, Esteva F, Godo L, Torra V.  2004.  On learning similarity relations in fuzzy case-based reasoning. Lecture Notes in Computer Science. 3135:14-32.
Armengol E.  1999.  Explanation-based Learning.
Armengol E.  2007.  Discovering plausible explanations of carcinogenenecity in chemical compounds. Lecture Notes in Artificial Intelligence. 4571:756-769.
Armengol E, Plaza E.  1997.  Induction of Feature Terms with INDIE. Future Generation Computer Systems Journal. 12:173-188.
Armengol E, Plaza E.  2003.  Discovery of toxicological patterns with lazy learning. Lecture Notes in Computer Science. Lecture Notes in Artificial Intelligence. 2774:919-926.
Armengol E, Dellunde P, García-Cerdaña A.  2016.  On similarity in fuzzy description logics. Fuzzy Sets and Systems. 292:49–74.
Armengol E, Ontañón S, Plaza E.  2004.  Explaining Similarity in CBR. Proceedigs of the ECCBR 2004 Workshops. 7th. European Conference on Case-Based Reasoning Madrid, Spain 30th. Augoust- 2nd September 2004. :87-95.