Proceedings of the KI 2015 Workshop on Formal and Cognitive Reasoning

This paper addresses the issue of creating agents that are able to learn rules for cooperative problem solving behavior in different multi-agent scenarios. The proposed agents start with given rule fragments that are combined to rules determining their action selection. The agents learn how to apply these rules adequately by collecting rewards retrieved from the simulation environment of the scenarios. To evaluate the approach, the resulting agents are applied in two different example scenarios.

[1]  Zoran Ognjanovic,et al.  A first-order conditional probability logic , 2012, Log. J. IGPL.

[2]  A. Church.  On Carnap's Analysis of Statements of Assertion and Belief , 1950 .

[3]  Sjur Dyrkolbotn.  How to Argue for Anything: Enforcing Arbitrary Sets of Labellings using AFs , 2014, KR.

[4]  Johanna Völker,et al.  A Framework for Ontology Learning and Data-driven Change Discovery , 2005 .

[5]  Lotfi A. Zadeh,et al.  Syllogistic reasoning in fuzzy logic and its application to usuality and reasoning with dispositions , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[6]  Pietro Baroni,et al.  SCC-recursiveness: a general schema for argumentation semantics , 2005, Artif. Intell..

[7]  Bora I. Kumova,et al.  Algorithmic Decision of Syllogisms , 2010, IEA/AIE.

[8]  Umberto Straccia,et al.  Managing uncertainty and vagueness in description logics for the Semantic Web , 2008, J. Web Semant..

[9]  Martin Diller,et al.  An Extension-Based Approach to Belief Revision in Abstract Argumentation , 2015, IJCAI.

[10]  L. A. Zadeh,et al.  Fuzzy logic and approximate reasoning , 1975, Synthese.

[11]  Raymond Reiter,et al.  A Logic for Default Reasoning , 1987, Artif. Intell..

[12]  Sven Ove Hansson.  Kernel Contraction , 1994, J. Symb. Log..

[13]  Petr Hájek,et al.  The liar paradox and fuzzy logic , 2000, Journal of Symbolic Logic.

[14]  Haythem O. Ismail.  A reason maintenance perspective on relevant Ramsey conditionals , 2010, Log. J. IGPL.

[15]  Nicholas J. J. Smith.  Vagueness and Degrees of Truth , 2008 .

[16]  Haythem O. Ismail.  LogAB: A first-order, non-paradoxical, algebraic logic of belief , 2012, Log. J. IGPL.

[17]  Terence Parsons,et al.  ON DENOTING PROPOSITIONS AND FACTS , 1993 .

[18]  Umberto Straccia,et al.  Reasoning with the finitely many-valued Lukasiewicz fuzzy Description Logic SROIQ , 2011, Inf. Sci..

[19]  Bora I. Kumova,et al.  Truth ratios of syllogistic moods , 2015, 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

[20]  Dov M. Gabbay,et al.  A Logical Account of Formal Argumentation , 2009, Stud Logica.

[21]  John McCarthy,et al.  Circumscription - A Form of Non-Monotonic Reasoning , 1980, Artif. Intell..

[22]  Bora I. Kumova,et al.  The Fuzzy Syllogistic System , 2010, MICAI.

[23]  Umberto Straccia,et al.  fuzzyDL: An expressive fuzzy description logic reasoner , 2008, 2008 IEEE International Conference on Fuzzy Systems (IEEE World Congress on Computational Intelligence).

[24]  Didier Dubois,et al.  Possibilistic logic : a retrospective and prospective view , 2003 .

[25]  Pei Wang.  From Inheritance Relation to Non-Axiomatic Logic , 1994 .

[26]  Thomas Linsbichler,et al.  Characteristics of multiple viewpoints in abstract argumentation , 2014, Artif. Intell..

[27]  Juan Carlos Vidal,et al.  A fuzzy syllogistic reasoning schema for generalized quantifiers , 2014, Fuzzy Sets Syst..

[28]  Pei Wang.  Reference Classes and Multiple Inheritances , 1995, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[29]  Paul E. Dunne,et al.  Semi-stable semantics , 2006, J. Log. Comput..

[30]  Fernando Bobillo,et al.  DeLorean: A Reasoner for Fuzzy OWL 1.1 , 2008, URSW.

[31]  Stanley Burris,et al.  A course in universal algebra , 1981, Graduate texts in mathematics.

[32]  Phan Minh Dung,et al.  On the Acceptability of Arguments and its Fundamental Role in Nonmonotonic Reasoning, Logic Programming and n-Person Games , 1995, Artif. Intell..

[33]  Stuart C. Shapiro,et al.  Belief spaces as sets of propositions , 1993, J. Exp. Theor. Artif. Intell..

[34]  Saul A. Kripke,et al.  Outline of a Theory of Truth , 1975 .

[35]  Boris Motik,et al.  Hypertableau Reasoning for Description Logics , 2009, J. Artif. Intell. Res..

[36]  Trevor J. M. Bench-Capon,et al.  Metalevel argumentation , 2011, J. Log. Comput..

[37]  Martin Caminada,et al.  On the evaluation of argumentation formalisms , 2007, Artif. Intell..

[38]  Joseph Y. Halpern.  Reasoning about uncertainty , 2003 .

[39]  Bora I. Kumova,et al.  Ontology-Based Fuzzy-Syllogistic Reasoning , 2015, IEA/AIE.

[40]  Bart Verheij,et al.  Two Approaches to Dialectical Argumentation: Admissible Sets and Argumentation Stages , 1999 .

[41]  Didier Dubois,et al.  Weighted logics for artificial intelligence - an introductory discussion , 2014, Int. J. Approx. Reason..

[42]  Guilin Qi,et al.  A Possibilistic Extension of Description Logics , 2007, Description Logics.

[43]  Haythem O. Ismail.  Stability in a Commonsense Ontology of States , 2013 .

[44]  Bora I. Kumova.  Generating Ontologies from Relational Data with Fuzzy-Syllogistic Reasoning , 2015, BDAS.

[45]  Marilde Terezinha Prado Santos,et al.  Combining Fuzzy Ontology Reasoning and Mamdani Fuzzy Inference System with HyFOM Reasoner , 2013, ICEIS.

[46]  Pietro Baroni,et al.  An introduction to argumentation semantics , 2011, The Knowledge Engineering Review.

[47]  N. Belnap,et al.  The Revision Theory of Truth , 1993 .

[48]  Peter Gärdenfors,et al.  On the logic of theory change: Partial meet contraction and revision functions , 1985, Journal of Symbolic Logic.

[49]  Pietro Baroni,et al.  On principle-based evaluation of extension-based argumentation semantics , 2007, Artif. Intell..

[50]  George Bealer,et al.  Theories of properties, relations, and propositions , 1979 .

[51]  P. L. Peterson.  Intermediate Quantities , 2020 .

[52]  Ben Goertzel,et al.  Probabilistic Logic Networks: A Comprehensive Framework for Uncertain Inference , 2008 .