The Complexity of Limited Belief Reasoning - The Quantifier-Free Case

The classical view of epistemic logic is that an agent knows all the logical consequences of their knowledge base. This assumption of logical omniscience is often unrealistic and makes reasoning computationally intractable. One approach to avoid logical omniscience is to limit reasoning to a certain belief level, which intuitively measures the reasoning "depth." This paper investigates the computational complexity of reasoning with belief levels. First we show that while reasoning remains tractable if the level is constant, the complexity jumps to PSPACE-complete -- that is, beyond classical reasoning -- when the belief level is part of the input. Then we further refine the picture using parameterized complexity theory to investigate how the belief level and the number of non-logical symbols affect the complexity.

[1]  Stefan Rümmele,et al.  The Parameterized Complexity of Positional Games , 2017, ICALP.

[2]  K. Konolige A deduction model of belief , 1986 .

[3]  Christoph Schwering,et al.  A Reasoning System for a First-Order Logic of Limited Belief , 2017, IJCAI.

[4]  Marcello D'Agostino An informational view of classical logic , 2015, Theor. Comput. Sci..

[5]  Jörg Flum,et al.  Parameterized Complexity Theory , 2006, Texts in Theoretical Computer Science. An EATCS Series.

[6]  Gerhard Lakemeyer,et al.  Decidable Reasoning in a Fragment of the Epistemic Situation Calculus , 2014, KR.

[7]  Christian Borgelt,et al.  Computational Intelligence , 2016, Texts in Computer Science.

[8]  Jaakko Hintikka,et al.  Impossible possible worlds vindicated , 1975, J. Philos. Log..

[9]  J. van Leeuwen,et al.  Theoretical Computer Science , 2003, Lecture Notes in Computer Science.

[10]  Jose M. Such,et al.  International Joint Conference on Artificial Intelligence (IJCAI) , 2016 .

[11]  Moshe Y. Vardi On Epistemic Logic and Logical Omniscience , 1986, TARK.

[12]  留美 種村 Awareness , 1995, Encyclopedia of Personality and Individual Differences.

[13]  Gerhard Lakemeyer,et al.  Decidable Reasoning in a Logic of Limited Belief with Function Symbols , 2016, KR.

[14]  Michael R. Fellows,et al.  Fixed-Parameter Tractability and Completeness IV: On Completeness for W[P] and PSPACE Analogues , 1995, Ann. Pure Appl. Log..

[15]  Gerhard Lakemeyer,et al.  Decidable Reasoning in a First-Order Logic of Limited Conditional Belief , 2016, ECAI.

[16]  Hector J. Levesque,et al.  A Logic of Implicit and Explicit Belief , 1984, AAAI.

[17]  Journal of automated reasoning , 1986 .

[18]  Nils J. Nilsson,et al.  Artificial Intelligence , 1974, IFIP Congress.

[19]  James P. Delgrande,et al.  A FRAMEWORK FOR LOGICS OF EXPLICIT BELIEF , 1995, Comput. Intell..

[20]  Gerhard Lakemeyer,et al.  A Logic of Limited Belief for Reasoning with Disjunctive Information , 2004, KR.

[21]  Sanjeev Arora,et al.  Computational Complexity: A Modern Approach , 2009 .

[22]  Gerhard Lakemeyer,et al.  Decidable Reasoning in a Logic of Limited Belief with Introspection and Unknown Individuals , 2013, IJCAI.

[23]  Stefan Szeider,et al.  Backdoors to Satisfaction , 2011, The Multivariate Algorithmic Revolution and Beyond.

[24]  Hector J. Levesque,et al.  Towards Tractable Inference for Resource-Bounded Agents , 2015, AAAI Spring Symposia.

[25]  Lenhart K. Schubert,et al.  A computational model of belief , 2000, Artif. Intell..

[26]  Ronald Fagin,et al.  Belief, Awareness, and Limited Reasoning. , 1987, Artif. Intell..

[27]  Yijia Chen,et al.  Machine-based methods in parameterized complexity theory , 2005, Theor. Comput. Sci..

[28]  Gerhard Lakemeyer,et al.  Limited Reasoning in First-Order Knowledge Bases , 1994, Artif. Intell..

[29]  Peter F. Patel-Schneider,et al.  A decidable first-order logic for knowledge representation , 1985, Journal of Automated Reasoning.