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A
Arcos JLluis, de Mántaras RLópez, Serra X.  1998.  Integrating background musical knowledge in a CBR system for generating expressive musical performances. AAAI'98 Workshop on CBR Integrations. :12-16.
Arcos JLluis, Plaza E.  2001.  Exploiting context awareness in information agents. 5th International Conference on Autonomous Agents. :116-117.
Argente E, Boissier O, Carrascosa C, Fornara N, Mcburney P, Noriega P, Ricci A, Sabater-Mir J., Schumacher MIgnaz, Tampitsikas C et al..  2013.  The role of the environment in agreement technologies. Artificial Intelligence Review. 39:21-38.
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., Manyà F.  2005.  Solving over-constrained problems with SAT technology. Lecture Notes in Computer Science. :1-15.
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., 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., 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.  2008.  A Preprocessor for Max-SAT Solvers. 11th International Conference on Theory and Applications of Satisfiability Testing (SAT-2008). 4996:15-20.
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., 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.  2010.  New Insights into Encodings from MaxCSP into Partial MaxSAT. 40th IEEE International Symposium on Multiple-Valued Logic (ISMVL). :46-52.
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., Manyà F.  2006.  Exact Max-SAT solvers for over-constrained problems. Journal of Heuristics. :375-392.
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.  2012.  Towards a Fuzzy Extension of the López de Mántaras Distance. IPMU 2012. 297:81-90.
Armengol E, Plaza E.  1995.  Explanation-based Learning: A Knowledge Level Analysis. AI Review. 9:19-35.
Armengol E.  1999.  Explanation-based Learning.
Armengol E.  2009.  Using explanations for determining carcinogenecity in chemical compounds. International Journal on Engineering Applications of Artificial Intelligence. 22:8.
Armengol E.  2008.  Building partial domain theories from explanations. Knowledge Intelligence. 2/08:19-24.
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.  2000.  Bottom-up induction of feature terms. Machine Learning Journal. 41:259-294.
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, Plaza E.  2006.  Symbolic explanation of similarities in case-based reasoning. Computing and Informatics. 25:153-171.
Armengol E.  2000.  Explanation-based Learning.
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, Dellunde P, García-Cerdaña A.  2014.  Local and Global Similarities in Fuzzy Class Theory.. CCIA'14. 269:205-217.
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.  2010.  On Similarities in Fuzzy Description Logics. Logic, Algebra and Truth Degrees 2010. 502:44-49.
Armengol E, Plaza E.  2005.  Lazy Learning for Predictive Toxicology based on a Chemical Ontology. Artificial Intelligence Methods and Tools for Systems Biology. :1-18.
Armengol E.  1998.  A Framework for Integrated Learning and Problem Solving.
Armengol E, Torra V.  2015.  Generalization-Based k-Anonymization. 5861:207-218.
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, García-Cerdaña A.  2010.  Lazy induction of descriptions using two fuzzy versions of the Rand index. IPMU 2010. 80:396-405.
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, 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.  2011.  Classification of Melanomas in situ using Knowledge Discovery with Explained CBR. Artificial Intelligence in Medicine. 51:12.
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, Plaza E.  2003.  Relational Case-based Reasoning for Cancinogenic Activity Prediction. Artificial Intelligence Review. 20:121-141.
Armengol E, Plaza E.  1997.  Induction of Feature Terms with INDIE. Future Generation Computer Systems Journal. 12:173-188.
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.  2004.  Multiple-instance case-based learning for predictive toxicology. Lecture Notes in Computer Science. 3303:206-220.
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.
Armengol E, Plaza E.  2005.  Using Symbolic Descriptions to Explain Similarity on CBR. Artificial intelligence research and development (CCIA-2005). :239-246.
Armengol E.  2007.  Discovering plausible explanations of carcinogenenecity in chemical compounds. Lecture Notes in Artificial Intelligence. 4571:756-769.
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, Dellunde P, García-Cerdaña A.  2016.  On similarity in fuzzy description logics. Fuzzy Sets and Systems. 292:49–74.
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.