The proof algorithms of plausible logic form a hierarchy

Authors:
David Billington
Affiliations:
School of Information and Communication Technology, Griffith University, Brisbane, Queensland, Australia
Venue:
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
Year:
2005

Citing 1
Cited 6

Argumentation Semantics for Defeasible Logic

Journal of Logic and Computation

Using Temporal Consistency to Improve Robot Localisation

RoboCup 2006: Robot Soccer World Cup X
Propositional Clausal Defeasible Logic

JELIA '08 Proceedings of the 11th European conference on Logics in Artificial Intelligence
Architecture for Hybrid Robotic Behavior

HAIS '09 Proceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems
Modelling behaviour requirements for automatic interpretation, simulation and deployment

SIMPAR'10 Proceedings of the Second international conference on Simulation, modeling, and programming for autonomous robots
A dynamic metalogic argumentation framework implementation

RuleML'2011 Proceedings of the 5th international conference on Rule-based reasoning, programming, and applications
A fixed-point semantics for plausible logic

AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence

Quantified Score

Hi-index	0.00

Visualization

Abstract

Plausible Logic is a non-monotonic logic with an efficient implementation. Plausible Logic has five proof algorithms, one is monotonic and four are non-monotonic. These five proof algorithms form a hierarchy. Ambiguity propagating proof algorithms are less risky than ambiguity blocking proof algorithms. The hierarchy shows that the benefit of using the riskier algorithms is that more formulas can be proved. Unlike previous Plausible Logics, the Plausible Logic in this paper is relatively consistent, checks for loops, can prove all its facts and all tautologies, and allows countably many formulas and rules to be considered.