Aleatoric dynamic epistemic logic for learning agents

Tim French, Andrew Gozzard, Mark Reynolds

Research output: Chapter in Book/Conference paperConference paper

Abstract

We propose a generalisation of dynamic epistemic logic, where propositions are aleatoric: that is, rather than having true/false values, propositions have odds of being true. Agents in such a system suppose a probability distribution of possible worlds, and based on observations are able to refine this probability distribution to match their observations. We demonstrate this logic with respect to some games of chance.

Original languageEnglish
Title of host publicationPRICAI 2019
Subtitle of host publicationTrends in Artificial Intelligence - 16th Pacific Rim International Conference on Artificial Intelligence, Proceedings
EditorsAbhaya C. Nayak, Alok Sharma
PublisherSpringer-Verlag Berlin
Pages433-445
Number of pages13
ISBN (Print)9783030299071
DOIs
Publication statusPublished - 1 Jan 2019
Event16th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2019 - Yanuka Island, Fiji
Duration: 26 Aug 201930 Aug 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11670 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference16th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2019
CountryFiji
CityYanuka Island
Period26/08/1930/08/19

Fingerprint

Epistemic Logic
Dynamic Logic
Proposition
Probability distributions
Probability Distribution
Odds
Game
Logic
Demonstrate
Learning
Observation
False
Generalization

Cite this

French, T., Gozzard, A., & Reynolds, M. (2019). Aleatoric dynamic epistemic logic for learning agents. In A. C. Nayak, & A. Sharma (Eds.), PRICAI 2019: Trends in Artificial Intelligence - 16th Pacific Rim International Conference on Artificial Intelligence, Proceedings (pp. 433-445). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11670 LNAI). Springer-Verlag Berlin. https://doi.org/10.1007/978-3-030-29908-8_35
French, Tim ; Gozzard, Andrew ; Reynolds, Mark. / Aleatoric dynamic epistemic logic for learning agents. PRICAI 2019: Trends in Artificial Intelligence - 16th Pacific Rim International Conference on Artificial Intelligence, Proceedings. editor / Abhaya C. Nayak ; Alok Sharma. Springer-Verlag Berlin, 2019. pp. 433-445 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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French, T, Gozzard, A & Reynolds, M 2019, Aleatoric dynamic epistemic logic for learning agents. in AC Nayak & A Sharma (eds), PRICAI 2019: Trends in Artificial Intelligence - 16th Pacific Rim International Conference on Artificial Intelligence, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11670 LNAI, Springer-Verlag Berlin, pp. 433-445, 16th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2019, Yanuka Island, Fiji, 26/08/19. https://doi.org/10.1007/978-3-030-29908-8_35

Aleatoric dynamic epistemic logic for learning agents. / French, Tim; Gozzard, Andrew; Reynolds, Mark.

PRICAI 2019: Trends in Artificial Intelligence - 16th Pacific Rim International Conference on Artificial Intelligence, Proceedings. ed. / Abhaya C. Nayak; Alok Sharma. Springer-Verlag Berlin, 2019. p. 433-445 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11670 LNAI).

Research output: Chapter in Book/Conference paperConference paper

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French T, Gozzard A, Reynolds M. Aleatoric dynamic epistemic logic for learning agents. In Nayak AC, Sharma A, editors, PRICAI 2019: Trends in Artificial Intelligence - 16th Pacific Rim International Conference on Artificial Intelligence, Proceedings. Springer-Verlag Berlin. 2019. p. 433-445. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-030-29908-8_35