Abstraction of Nondeterministic Situation Calculus Action Theories

Authors: Bita Banihashemi, Giuseppe De Giacomo, Yves Lesperance

IJCAI 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical We develop a general framework for abstracting the behavior of an agent that operates in a nondeterministic domain, i.e., where the agent does not control the outcome of the nondeterministic actions, based on the nondeterministic situation calculus and the Con Golog programming language. This paper presents foundational results, i.e., a generic framework for abstraction in nondeterministic domains, which can be used for many reasoning tasks, such as planning, execution monitoring, and explanation.
Researcher Affiliation Academia Bita Banihashemi1 , Giuseppe De Giacomo2 , Yves Lesp erance3 1Ronin Institute 2University of Oxford 3York University bita@ronininstitute.org, giuseppe.degiacomo@cs.ox.ac.uk, lesperan@eecs.yorku.ca
Pseudocode No No, the paper defines formal logical expressions and language constructs but does not contain explicitly labeled 'Pseudocode' or 'Algorithm' blocks.
Open Source Code No No, the paper does not contain any statement about releasing source code or provide links to a code repository.
Open Datasets No No, the paper uses a conceptual 'Triangle Tireworld' as a running example for illustrative purposes, but this is not a public dataset. The text states: 'Our running example is based on a triangle tireworld domain (see Fig. 1).'
Dataset Splits No No, the paper does not conduct empirical experiments with datasets, and therefore does not provide information on training, validation, or test splits.
Hardware Specification No No, the paper is theoretical and does not describe any computational experiments or hardware used.
Software Dependencies No No, the paper mentions the 'Con Golog programming language' and 'situation calculus' as part of its theoretical framework, but does not list specific software dependencies with version numbers for experimental reproducibility.
Experiment Setup No No, the paper is theoretical and does not describe experimental setups, hyperparameters, or training configurations.