A Logical Theory of Localization

Studia Logica 104 (4):741-772 (2016)
  Copy   BIBTEX

Abstract

A central problem in applying logical knowledge representation formalisms to traditional robotics is that the treatment of belief change is categorical in the former, while probabilistic in the latter. A typical example is the fundamental capability of localization where a robot uses its noisy sensors to situate itself in a dynamic world. Domain designers are then left with the rather unfortunate task of abstracting probabilistic sensors in terms of categorical ones, or more drastically, completely abandoning the inner workings of sensors to black-box probabilistic tools and then interpreting their outputs in an abstract way. Building on a first-principles approach by Bacchus, Halpern and Levesque, and a recent continuous extension to it by Belle and Levesque, we provide an axiomatization that shows how localization can be realized wrt a basic action theory, thereby demonstrating how such capabilities can be enabled in a single logical framework. We then show how the framework can also enable localization for multiple agents, where an agent can appeal to the sensing already performed by another agent and the knowledge of their relative positions to localize itself.

Links

PhilArchive



    Upload a copy of this work     Papers currently archived: 90,616

External links

Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

Similar books and articles

Using abstract resources to control reasoning.Richard W. Weyhrauch, Marco Cadoli & Carolyn L. Talcott - 1998 - Journal of Logic, Language and Information 7 (1):77-101.
Reasoning about Knowledge and Belief: A Syntactical Treatment.Maria Fasli - 2003 - Logic Journal of the IGPL 11 (2):247-284.
Dynamic Epistemic Logic and Logical Omniscience.Mattias Skipper Rasmussen - 2015 - Logic and Logical Philosophy 24 (3):377-399.
Logical omniscience as infeasibility.Sergei Artemov & Roman Kuznets - 2014 - Annals of Pure and Applied Logic 165 (1):6-25.
How to use probabilities in reasoning.John L. Pollock - 1991 - Philosophical Studies 64 (1):65 - 85.
Second-order reasoning in description logics.Andrzej Szalas - 2006 - Journal of Applied Non-Classical Logics 16 (3-4):517-530.
Perception and non-inferential knowledge of action.Thor Grünbaum - 2011 - Philosophical Explorations 14 (2):153 - 167.
Term-modal logics.Melvin Fitting, Lars Thalmann & Andrei Voronkov - 2001 - Studia Logica 69 (1):133-169.
Knowledge in Action.Jonathan Weisberg - 2013 - Philosophers' Imprint 13.
Models and minds.Stuart C. Shapiro & William J. Rapaport - 1991 - In Robert E. Cummins & John L. Pollock (eds.), Philosophy and AI. Cambridge: MIT Press. pp. 215--259.

Analytics

Added to PP
2015-08-23

Downloads
11 (#976,244)

6 months
3 (#447,120)

Historical graph of downloads
How can I increase my downloads?