From First-Order Logic to Assertional Logic

First-Order Logic (FOL) is widely regarded as the foundation of knowledge representation. Nevertheless, in this paper, we argue that FOL has several critical issues for this purpose. Instead, we propose an alternative called assertional logic, in which all syntactic objects are categorized as set theoretic constructs including individuals, concepts and operators, and all kinds of knowledge are formalized by equality assertions. We first present a primitive form of assertional logic that uses minimal assumed knowledge and constructs. Then, we show how to extend it by definitions, which are special kinds of knowledge, i.e., assertions. We argue that assertional logic, although simpler, is more expressive and extensible than FOL. As a case study, we show how assertional logic can be used to unify logic and probability.

[1]  Edmund M. Clarke,et al.  Design and Synthesis of Synchronization Skeletons Using Branching Time Temporal Logic , 2008, 25 Years of Model Checking.

[2]  Franz Baader,et al.  A Scheme for Integrating Concrete Domains into Concept Languages , 1991, IJCAI.

[3]  Diego Calvanese,et al.  The Description Logic Handbook: Theory, Implementation, and Applications , 2003, Description Logic Handbook.

[4]  Judea Pearl,et al.  Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.

[5]  H. Gaifman Concerning measures in first order calculi , 1964 .

[6]  Bernhard Nebel,et al.  Task Planning for an Autonomous Service Robot , 2010, KI.

[7]  Matthew Richardson,et al.  Markov logic networks , 2006, Machine Learning.

[8]  Alexander Borgida,et al.  Extensible Knowledge Representation: the Case of Description Reasoners , 2011, J. Artif. Intell. Res..

[9]  Hector J. Levesque,et al.  Foundations for the Situation Calculus , 1998, Electron. Trans. Artif. Intell..

[10]  Hector J. Levesque,et al.  Knowledge Representation and Reasoning , 2004 .

[11]  Fangzhen Lin,et al.  Situation Calculus , 2008, Handbook of Knowledge Representation.

[12]  Joseph Y. Halpern An Analysis of First-Order Logics of Probability , 1989, IJCAI.

[13]  Maurizio Lenzerini,et al.  Higher-Order Description Logics for Domain Metamodeling , 2011, AAAI.

[14]  Stuart J. Russell,et al.  Probabilistic models with unknown objects , 2006 .

[15]  Fahiem Bacchus,et al.  Representing and reasoning with probabilistic knowledge - a logical approach to probabilities , 1991 .

[16]  James F. Allen Maintaining knowledge about temporal intervals , 1983, CACM.

[17]  Amir Pnueli,et al.  The temporal logic of programs , 1977, 18th Annual Symposium on Foundations of Computer Science (sfcs 1977).

[18]  Michael Thielscher GDL-III: A Proposal to Extend the Game Description Language to General Epistemic Games , 2016, ECAI.

[19]  Theodore Hailperin,et al.  Probability logic , 1984, Notre Dame J. Formal Log..

[20]  Carsten Lutz,et al.  E-connections of abstract description systems , 2004, Artif. Intell..