Revising Beliefs and Intentions in Stochastic Environments

Authors: Nima Motamed, Natasha Alechina, Mehdi Dastani, Dragan Doder

IJCAI 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical In this paper, we initiate the study of belief and intention revision in stochastic environments, where an agent s beliefs and intentions are specified in a decidable probabilistic temporal logic. We then provide general Katsuno & Mendelzon-style representation theorems for both belief and intention revision, giving clear semantic characterizations of revision methods.
Researcher Affiliation Academia 1Utrecht University, The Netherlands 2Open University, The Netherlands {n.motamed, n.a.alechina, m.m.dastani, d.doder}@uu.nl
Pseudocode No The paper presents theoretical definitions, logic syntax, semantics, and proofs, but does not include any pseudocode or algorithm blocks.
Open Source Code No The paper is a theoretical work and does not mention releasing any source code for its described methodologies.
Open Datasets No The paper is theoretical and does not involve experimental evaluation with datasets.
Dataset Splits No The paper is theoretical and does not involve experimental evaluation with dataset splits.
Hardware Specification No The paper is theoretical and does not describe any experimental hardware specifications.
Software Dependencies No The paper is theoretical and does not specify any software dependencies with version numbers required for experimental replication.
Experiment Setup No The paper is theoretical and does not describe any experimental setup details or hyperparameters.