Abstraction in Situation Calculus Action Theories

Authors: Bita Banihashemi, Giuseppe De Giacomo, Yves Lesperance

AAAI 2017 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical We develop a general framework for agent abstraction based on the situation calculus and the Con Golog agent programming language. We assume that we have a high-level specification and a low-level specification of the agent, both represented as basic action theories. A refinement mapping specifies how each high-level action is implemented by a lowlevel Con Golog program and how each high-level fluent can be translated into a low-level formula. We define a notion of sound abstraction between such action theories in terms of the existence of a suitable bisimulation between their respective models. Sound abstractions have many useful properties that ensure that we can reason about the agent s actions (e.g., executability, projection, and planning) at the abstract level, and refine and concretely execute them at the low level. We also characterize the notion of complete abstraction where all actions (including exogenous ones) that the high level thinks can happen can in fact occur at the low level.
Researcher Affiliation Academia Bita Banihashemi York University Toronto, Canada bita@cse.yorku.ca Giuseppe De Giacomo Sapienza Universit a di Roma Roma, Italy degiacomo@dis.uniroma1.it Yves Lesp erance York University Toronto, Canada lesperan@cse.yorku.ca
Pseudocode No The paper defines programming language constructs (e.g., 'δ ::= α | ϕ? | δ1; δ2 | δ1|δ2 | πx.δ | δ | δ1 δ2') but does not include any explicitly labeled pseudocode or algorithm blocks with structured steps for a procedure.
Open Source Code No The paper does not contain any statement or link indicating that the source code for the described methodology is publicly available.
Open Datasets No The paper uses a 'simple logistics domain' as a running example for illustrating its theoretical concepts but does not refer to or provide access information for a public dataset used in empirical training.
Dataset Splits No The paper focuses on theoretical development and does not describe empirical experiments with dataset splits for training, validation, or testing.
Hardware Specification No The paper is theoretical and focuses on developing a framework; it does not describe any experiments that would require specific hardware, thus no hardware specifications are provided.
Software Dependencies No The paper describes a theoretical framework (situation calculus, Con Golog) but does not list specific software dependencies with version numbers that would be required to reproduce any implementation or experimental results.
Experiment Setup No The paper is theoretical and does not describe any empirical experimental setup, including hyperparameters, training configurations, or system-level settings.