Expressivity of Planning with Horn Description Logic Ontologies
(Technical Report)
- URL: http://arxiv.org/abs/2203.09361v1
- Date: Thu, 17 Mar 2022 14:50:06 GMT
- Title: Expressivity of Planning with Horn Description Logic Ontologies
(Technical Report)
- Authors: Stefan Borgwardt, J\"org Hoffmann, Alisa Kovtunova, Markus Kr\"otzsch,
Bernhard Nebel, Marcel Steinmetz
- Abstract summary: We address open-world state constraints formalized by planning over a description logic (DL) ontology.
We propose a novel compilation scheme into standard PDDL with derived predicates.
We show that our approach can outperform previous work on existing benchmarks for planning with DL.
- Score: 12.448670165713652
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: State constraints in AI Planning globally restrict the legal environment
states. Standard planning languages make closed-domain and closed-world
assumptions. Here we address open-world state constraints formalized by
planning over a description logic (DL) ontology. Previously, this combination
of DL and planning has been investigated for the light-weight DL DL-Lite. Here
we propose a novel compilation scheme into standard PDDL with derived
predicates, which applies to more expressive DLs and is based on the
rewritability of DL queries into Datalog with stratified negation. We also
provide a new rewritability result for the DL Horn-ALCHOIQ, which allows us to
apply our compilation scheme to quite expressive ontologies. In contrast, we
show that in the slight extension Horn-SROIQ no such compilation is possible
unless the weak exponential hierarchy collapses. Finally, we show that our
approach can outperform previous work on existing benchmarks for planning with
DL ontologies, and is feasible on new benchmarks taking advantage of more
expressive ontologies. That is an extended version of a paper accepted at AAAI
22.
Related papers
- LINC: A Neurosymbolic Approach for Logical Reasoning by Combining
Language Models with First-Order Logic Provers [60.009969929857704]
Logical reasoning is an important task for artificial intelligence with potential impacts on science, mathematics, and society.
In this work, we reformulating such tasks as modular neurosymbolic programming, which we call LINC.
We observe significant performance gains on FOLIO and a balanced subset of ProofWriter for three different models in nearly all experimental conditions we evaluate.
arXiv Detail & Related papers (2023-10-23T17:58:40Z) - Towards Ontology-Mediated Planning with OWL DL Ontologies (Extended
Version) [7.995360025953931]
We present a new approach in which the planning specification and ontology are kept separate, and are linked together using an interface.
This allows planning experts to work in a familiar formalism, while existing domains can be easily integrated and extended by experts.
The idea is to rewrite the whole-mediated planning problem into a classical planning problem to be processed by existing planning tools.
arXiv Detail & Related papers (2023-08-16T08:05:53Z) - DiNADO: Norm-Disentangled Neurally-Decomposed Oracles for Controlling Language Models [55.06442277395388]
NeurAlly-Decomposed Oracle (NADO) is a powerful approach for controllable generation with large language models.
Vanilla NADO suffers from vanishing gradient for low-probability control signals.
We propose a improved version of the NADO algorithm, namely DiNADO, which improves the performance of the NADO algorithm.
arXiv Detail & Related papers (2023-06-20T18:36:52Z) - Lattice-preserving $\mathcal{ALC}$ ontology embeddings [50.05281461410368]
We propose an order-preserving embedding method to generate embeddings on a graph out of We, the semantics of which are expressed in Logics Descriptions (DLs)
We show that our method outperforms state-the-art theory-of-of-the-art embedding methods in several knowledge base completion tasks.
arXiv Detail & Related papers (2023-05-11T22:27:51Z) - A Lightweight Constrained Generation Alternative for Query-focused
Summarization [8.264410236351111]
Query-focused summarization (QFS) aims to provide a summary of a document that satisfies information need of a given query.
We propose leveraging a recently developed constrained generation model Neurological Decoding (NLD) as an alternative to current QFS regimes.
We demonstrate the efficacy of this approach on two public QFS collections achieving near parity with the state-of-the-art model with substantially reduced complexity.
arXiv Detail & Related papers (2023-04-23T18:43:48Z) - Logic of Differentiable Logics: Towards a Uniform Semantics of DL [1.1549572298362787]
Differentiable logics (DLs) have been proposed as a method of training neural networks to satisfy logical specifications.
This paper proposes a meta-language for defining DLs that we call the Logic of Differentiable Logics, or LDL.
We use LDL to establish several theoretical properties of existing DLs, and to conduct their empirical study in neural network verification.
arXiv Detail & Related papers (2023-03-19T13:03:51Z) - Forward LTLf Synthesis: DPLL At Work [1.370633147306388]
We propose a new AND-OR graph search framework for synthesis of Linear Temporal Logic on finite traces (LTLf)
Within such framework, we devise a procedure inspired by the Davis-Putnam-Logemann-Loveland (DPLL) algorithm to generate the next available agent-environment moves.
We also propose a novel equivalence check for search nodes based on syntactic equivalence of state formulas.
arXiv Detail & Related papers (2023-02-27T14:33:50Z) - Linear Temporal Logic Modulo Theories over Finite Traces (Extended
Version) [72.38188258853155]
This paper studies Linear Temporal Logic over Finite Traces (LTLf)
proposition letters are replaced with first-order formulas interpreted over arbitrary theories.
The resulting logic, called Satisfiability Modulo Theories (LTLfMT), is semi-decidable.
arXiv Detail & Related papers (2022-04-28T17:57:33Z) - SMT-Based Safety Verification of Data-Aware Processes under Ontologies
(Extended Version) [71.12474112166767]
We introduce a variant of one of the most investigated models in this spectrum, namely simple artifact systems (SASs)
This DL, enjoying suitable model-theoretic properties, allows us to define SASs to which backward reachability can still be applied, leading to decidability in PSPACE of the corresponding safety problems.
arXiv Detail & Related papers (2021-08-27T15:04:11Z) - Defeasible reasoning in Description Logics: an overview on DL^N [10.151828072611426]
We provide an overview on DLN, illustrating the underlying knowledge engineering requirements as well as the characteristic features that preserve DLN from some recurrent semantic and computational drawbacks.
We also compare DLN with some alternative nonmonotonic semantics, enlightening the relationships between the KLMs and DLN.
arXiv Detail & Related papers (2020-09-10T16:30:30Z) - Logical Natural Language Generation from Open-Domain Tables [107.04385677577862]
We propose a new task where a model is tasked with generating natural language statements that can be emphlogically entailed by the facts.
To facilitate the study of the proposed logical NLG problem, we use the existing TabFact dataset citechen 2019tabfact featured with a wide range of logical/symbolic inferences.
The new task poses challenges to the existing monotonic generation frameworks due to the mismatch between sequence order and logical order.
arXiv Detail & Related papers (2020-04-22T06:03:10Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.