higher-order logic
Enabling Secure and Ephemeral AI Workloads in Data Mesh Environments
Many large enterprises that operate highly governed and complex ICT environments have no efficient and effective way to support their Data and AI teams in rapidly spinning up and tearing down self-service data and compute infrastructure, to experiment with new data analytic tools, and deploy data products into operational use. This paper proposes a key piece of the solution to the overall problem, in the form of an on-demand self-service data-platform infrastructure to empower de-centralised data teams to build data products on top of centralised templates, policies and governance. The core innovation is an efficient method to leverage immutable container operating systems and infrastructure-as-code methodologies for creating, from scratch, vendor-neutral and short-lived Kubernetes clusters on-premises and in any cloud environment. Our proposed approach can serve as a repeatable, portable and cost-efficient alternative or complement to commercial Platform-as-a-Service (PaaS) offerings, and this is particularly important in supporting interoperability in complex data mesh environments with a mix of modern and legacy compute infrastructure.
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Faithful Logic Embeddings in HOL -- A recipe to have it all: deep and shallow, automated and interactive, heavy and light, proofs and counterexamples, meta and object level
Deep and shallow embeddings of non-classical logics in classical higher-order logic have been explored, implemented, and used in various automated reasoning tools in recent years. This paper presents a recipe for the simultaneous deployment of different forms of deep and shallow embeddings in classical higher-order logic, enabling not only flexible interactive and automated theorem proving and counterexample finding at meta and object level, but also automated faithfulness proofs between the logic embeddings. The approach, which is fruitful for logic education, research and application, is deliberately illustrated here using simple propositional modal logic. However, the work presented is conceptual in nature and not limited to such a simple logic context. Keywords: Logic embeddings Faithfulness Automated Reasoning 1 Motivation and Introduction Deep embeddings of logics, or more generally of domain-specific languages, in a suitable metalogic, such as the classical higher-order logic (HOL) [23,4], are typically based on explicitly introduced abstract data types that essentially axioma-tize the inductively defined character of the new language.
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Teaching Higher-Order Logic Using Isabelle
Lund, Simon Tobias, Villadsen, Jørgen
Higher-order logic, also known as simple type theory [3], has been described as the combination of functional programming and logic [9], and has proved a very powerful tool for the formalization of mathematics and computer science. It is an expressive enough logic to cover a wide array of fields, while still being built on relatively simple principles, and a number of proof assistants based on higher-order logic are available. We consider formal reasoning in the generic proof assistant Isabelle [10, 11]. In the present paper we are taking advantage of the genericity of Isabelle, but we also find that Isabelle is at least as user-friendly and intuitive as other proof assistants of comparable power. Although Isabelle is generic and comes with a number of object logics like first-order logic (FOL) and axiomatic set theory (ZF), the default object logic is higher-order logic, called Isabelle/HOL.
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A Formalisation of Abstract Argumentation in Higher-Order Logic
Steen, Alexander, Fuenmayor, David
We present an approach for representing abstract argumentation frameworks based on an encoding into classical higher-order logic. This provides a uniform framework for computer-assisted assessment of abstract argumentation frameworks using interactive and automated reasoning tools. This enables the formal analysis and verification of meta-theoretical properties as well as the flexible generation of extensions and labellings with respect to well-known argumentation semantics.
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Superposition with Lambdas
Bentkamp, Alexander, Blanchette, Jasmin, Tourret, Sophie, Vukmirović, Petar, Waldmann, Uwe
To increase automation in proof assistants and other verification tools based on higher-order formalisms, we propose to generalize superposition to an extensional, polymorphic, clausal version of higher-order logic (also called simple type theory). Our ambition is to achieve a graceful extension, which coincides with standard superposition on first-order problems and smoothly scales up to arbitrary higher-order problems. Bentkamp, Blanchette, Cruanes, and Waldmann [12] designed a family of superpositionlike calculi for a λ-free clausal fragment of higher-order logic, with currying and applied variables. We adapt their extensional nonpurifying calculus to support λ-terms (Sect.
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Higher-order Logic as Lingua Franca -- Integrating Argumentative Discourse and Deep Logical Analysis
Fuenmayor, David, Benzmüller, Christoph
We present an approach towards the deep, pluralistic logical analysis of argumentative discourse that benefits from the application of state-of-the-art automated reasoning technology for classical higher-order logic. Thanks to its expressivity this logic can adopt the status of a uniform \textit{lingua franca} allowing the encoding of both formalized arguments (their deep logical structure) and dialectical interactions (their attack and support relations). We illustrate this by analyzing an excerpt from an argumentative debate on climate engineering. Another, novel contribution concerns the definition of abstract, language-theoretical foundations for the characterization and assessment of shallow semantical embeddings (SSEs) of non-classical logics in classical higher-order logic, which constitute a pillar stone of our approach. The novel perspective we draw enables more concise and more elegant characterizations of semantical embeddings of logics and logic combinations, which is demonstrated with several examples.
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Superposition for Lambda-Free Higher-Order Logic
Bentkamp, Alexander, Blanchette, Jasmin, Cruanes, Simon, Waldmann, Uwe
We introduce refutationally complete superposition calculi for intentional and extensional clausal $\lambda$-free higher-order logic, two formalisms that allow partial application and applied variables. The calculi are parameterized by a term order that need not be fully monotonic, making it possible to employ the $\lambda$-free higher-order lexicographic path and Knuth-Bendix orders. We implemented the calculi in the Zipperposition prover and evaluated them on Isabelle/HOL and TPTP benchmarks. They appear promising as a stepping stone towards complete, highly efficient automatic theorem provers for full higher-order logic.
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Extensional Higher-Order Paramodulation in Leo-III
Steen, Alexander, Benzmüller, Christoph
Leo-III is an automated theorem prover for extensional type theory with Henkin semantics and choice. Reasoning with primitive equality is enabled by adapting paramodulation-based proof search to higher-order logic. The prover may cooperate with multiple external specialist reasoning systems such as first-order provers and SMT solvers. Leo-III is compatible with the TPTP/TSTP framework for input formats, reporting results and proofs, and standardized communication between reasoning systems, enabling e.g. proof reconstruction from within proof assistants such as Isabelle/HOL. Leo-III supports reasoning in polymorphic first-order and higher-order logic, in all normal quantified modal logics, as well as in different deontic logics. Its development had initiated the ongoing extension of the TPTP infrastructure to reasoning within non-classical logics.
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Graph Representations for Higher-Order Logic and Theorem Proving
Paliwal, Aditya, Loos, Sarah, Rabe, Markus, Bansal, Kshitij, Szegedy, Christian
This paper presents the first use of graph neural networks (GNNs) for higher-order proof search and demonstrates that GNNs can improve upon state-of-the-art results in this domain. Interactive, higher-order theorem provers allow for the formalization of most mathematical theories and have been shown to pose a significant challenge for deep learning. Higher-order logic is highly expressive and, even though it is well-structured with a clearly defined grammar and semantics, there still remains no well-established method to convert formulas into graph-based representations. In this paper, we consider several graphical representations of higher-order logic and evaluate them against the HOList benchmark for higher-order theorem proving.
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