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Towards a Logic for Reasoning About Learning in a Changing World

14 pagesPublished: May 15, 2012

Abstract

We develop an algebraic modal logic that combines epistemic and dynamic modalities with a view to modelling information acquisition (learning) by automated agents in a changing world. Unlike most treatments of dynamic epistemic logic, we have transitions that ``change the state'' of the underlying system and not just the state of knowledge of the agents. The key novel feature that emerges is the need to have a way of ``inverting transitions'' and distinguishing between transitions that ``really happen'' and transitions that are possible.

Our approach is algebraic, rather than being based on a Kripke-style semantics. The semantics are given in terms of quantales. We introduce a class of quantales with the appropriate inverse operations and use it to model toy robot-navigation problems, which illustrate how an agent learns information by taking actions. We discuss how a sound and complete logic of the algebra may be obtained from the positive fragment of PDL with converse.

Keyphrases: algebraic modal logic, dynamic epistemic logic, information learning, quantale module, robot navigation

In: Berndt Müller (editor). LAM'10. 3rd International Workshop on Logics, Agents, and Mobility, vol 7, pages 82-95.

BibTeX entry
@inproceedings{LAM'10:Towards_Logic_Reasoning_About,
  author    = {Prakash Panangaden and Mehrnoosh Sadrzadeh},
  title     = {Towards a Logic for Reasoning About Learning in a Changing World},
  booktitle = {LAM'10. 3rd International Workshop on Logics, Agents, and Mobility},
  editor    = {Berndt Müller},
  series    = {EPiC Series in Computing},
  volume    = {7},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {/publications/paper/sx6F},
  doi       = {10.29007/8g5j},
  pages     = {82-95},
  year      = {2012}}
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