Abstract Deep and shallow embeddings of non-classical logics in classical higher-order logic have been explored, implemented, and used in various reasoning tools in recent years. This paper presents a method for the simultaneous deployment of deep and shallow embeddings of various degrees in classical higher-order logic. This enables flexible, interactive and automated theorem proving and counterexample finding at meta and object level, as well as automated faithfulness proofs between these logic embeddings. The method is beneficial for logic education, research and application and is illustrated here using a simple propositional modal logic. However, this approach is conceptual in nature and not limited to this simple logic context.

It is not straightforward to reason about specific legal concepts such as epistemic rights and duties, which are crucial in AI systems that have to make autonomous decisions based on who knows what, who is entitled to know, and under what conditions information should be shared or withheld. Such issues are central to responsible AI, data governance, and regulatory compliance. A concrete application arises is in the context of the GDPR, where a data subject has a right to know whether and for what purpose her personal data is being processed, creating a duty to tell for the controller when asked. On the other hand, if the software used for the processing is proprietary, the data subject does not have the right to know its exact mechanisms, so her asking to know them does not create a corresponding duty for the data controller. In this paper, a shallow semantical embedding (SSE) of the Dynamic Logic of the Right to Know (LRK) in Higher-Order Logic is presented. The embedding is proven faithful, and it is encoded and experimented with in the Isabelle/HOL proof assistant. The SSE is then used to reason with the GDPR example encoded in LRK. The embedding of LRK differs from existing ones in how it represents the dynamic updating of the model: instead of performing changes on the domain of possible worlds, the provided SSE maintains the accessibility and neighborhood relations within the context of a formula. Updates are then handled by updating the relations, while the domain of possible worlds stays the same. The work presented in this paper contributes to the LogiKEy knowledge engineering methodology and framework, which enables experimentation with logics and logic combinations, with general and domain knowledge, and with concrete use cases.

The paper presents a comprehensive analysis of the European AI Act in terms of its logical modalities, with the aim of preparing its formal representation, for example, within the logic-pluralistic Knowledge Engineering Framework and Methodology (LogiKEy). LogiKEy develops computational tools for normative reasoning based on formal methods, employing Higher-Order Logic (HOL) as a unifying meta-logic to integrate diverse logics through shallow semantic embeddings. This integration is facilitated by Isabelle/HOL, a proof assistant tool equipped with several automated theorem provers. The modalities within the AI Act and the logics suitable for their representation are discussed. For a selection of these logics, embeddings in HOL are created, which are then used to encode sample paragraphs. Initial experiments evaluate the suitability of these embeddings for automated reasoning, and highlight key challenges on the way to more robust reasoning capabilities.

Abstract Higher-order logic HOL offers a very simple syntax and semantics for representing and reasoning about typed data structures. But its type system lacks advanced features where types may depend on terms. Dependent type theory offers such a rich type system, but has rather substantial conceptual differences to HOL, as well as comparatively poor proof automation support. We introduce a dependently-typed extension DHOL of HOL that retains the style and conceptual framework of HOL. Moreover, we build a translation from DHOL to HOL and implement it as a preprocessor to a HOL theorem prover, thereby obtaining a theorem prover for DHOL.

This special issue of the Journal of Logic and Computation presents 11 carefully selected articles in the field of Logic and Argumentation. Authors of the strongest contributions to 4th International Conference on Logic and Argumentation (CLAR 2021) were invited to submit extended versions of their papers for inclusion in this special issue. All articles in this volume were carefully reviewed by two or three expert reviewers before acceptance was finally granted. CLAR 2021 was held in Hangzhou, 20–22 October 2021 at the Zhejiang University City College in China. This special issue was made possible by the numerous strong submissions (58 in total) we received for the conference, from which 30 presentations and 4 additional invited talks were selected for presentation at the conference and for publication in the CLAR 2021 proceedings published as volume 13040 in the Springer series Lecture Notes in Computer Science. The contributions to this special issue, and more generally to CLAR 2021, cover a wide range of topics that are the focus of the CLAR conference series, including in particular abstract and structured argumentation, logic and argumentation, argumentation with qualitative and quantitative uncertainty, knowledge representation and reasoning, modal and non-classical logics and non-monotonic logics, with applications in a variety of fields like law, ethics, game theory, linguistics and medical reasoning.

Abstract A shallow semantical embedding for public announcement logic (PAL) with relativized common knowledge is presented. This embedding enables the first-time automation of this logic with off-the-shelf theorem provers for classical higher-order logic. It is demonstrated (i) how meta-theoretical studies can be automated this way and (ii) how non-trivial reasoning in the target logic (PAL), required for instance to obtain a convincing encoding and automation of the wise men puzzle, can be realized. Key to the presented semantical embedding is that evaluation domains are modelled explicitly and treated as an additional parameter in the encodings of the constituents of the embedded target logic; in previous related works, e.g. on the embedding of normal modal logics, evaluation domains were implicitly shared between meta-logic and target logic. The work presented in this article constitutes an important addition to the pluralist LogiKEy knowledge engineering methodology, which enables experimentation with logics and their combinations, with general and domain knowledge, and with concrete use cases—all at the same time.

A modeloid, a certain set of partial bijections, emerges from the idea to abstract from a structure to the set of its partial automorphisms. It comes with an operation, called the derivative, which is inspired by Ehrenfeucht-Fraïssé games. In this paper we develop a generalization of a modeloid first to an inverse semigroup and then to an inverse category using an axiomatic approach to category theory. We then show that this formulation enables a purely algebraic view on Ehrenfeucht-Fraïssé games.

peer reviewed

An approach to universal (meta-)logical reasoning in classical higher-order logic is employed to explore and study simplifications of Kurt Gödel's modal ontological argument. Some argument premises are modified, others are dropped, modal collapse is avoided and validity is shown already in weak modal logics K and T. Key to the gained simplifications of Gödel's original theory is the exploitation of a link to the notions of filter and ultrafilter in topology. The paper illustrates how modern knowledge representation and reasoning technology for quantified non-classical logics can contribute new knowledge to other disciplines. The contributed material is also well suited to support teaching of non-trivial logic formalisms in classroom.

A shallow semantical embedding of free logic in classical higher-order logic is presented, which enables the off-the-shelf application of higher-order interactive and automated theorem provers for the formalisation and verification of free logic theories. Subsequently, this approach is applied to a selected domain of mathematics: starting from a generalization of the standard axioms for a monoid we present a stepwise development of various, mutually equivalent foundational axiom systems for category theory. As a side-effect of this work some (minor) issues in a prominent category theory textbook have been revealed. The purpose of this article is not to claim any novel results in category theory, but to demonstrate an elegant way to “implement” and utilize interactive and automated reasoning in free logic, and to present illustrative experiments.

The computer-mechanization of an ambitious explicit ethical theory, Gewirth’s Principle of Generic Consistency, is used to showcase an approach for representing and reasoning with ethical theories exhibiting complex logical features like alethic and deontic modalities, indexicals, higher-order quantification, among others. Harnessing the high expressive power of Church’s type theory as a meta-logic to semantically embed a combination of quantified non-classical logics, our work pushes existing boundaries in knowledge representation and reasoning. We demonstrate that intuitive encodings of complex ethical theories and their automation on the computer are no longer antipodes.

We present a procedure for algorithmically embedding problems formulated in higher- order modal logic into classical higher-order logic. The procedure was implemented as a stand-alone tool and can be used as a preprocessor for turning TPTP THF-compliant the- orem provers into provers for various modal logics. The choice of the concrete modal logic is thereby specified within the problem as a meta-logical statement. This specification for- mat as well as the underlying semantics parameters are discussed, and the implementation and the operation of the tool are outlined. By combining our tool with one or more THF-compliant theorem provers we accomplish the most widely applicable modal logic theorem prover available to date, i.e. no other available prover covers more variants of propositional and quantified modal logics. Despite this generality, our approach remains competitive, at least for quantified modal logics, as our experiments demonstrate.

Agent architectures and parallelization are, with a few exceptions, rarely to encounter in traditional automated theorem proving systems. This situation is motivating our ongoing work in the higher-order theorem prover Leo-III . In contrast to its predecessor – the well established prover LEO-II – and most other modern provers, Leo-III is designed from the very beginning for concurrent proof search. The prover features a multiagent blackboard architecture for reasoning agents to cooperate and to parallelize proof construction on the term, clause and search level.

Leo-II is an automated theorem prover for classical higher-order logic. The prover has pioneered cooperative higher-order-first-order proof automation, it has influenced the development of the TPTP THF infrastructure for higher-order logic, and it has been applied in a wide array of problems. Leo-II may also be called in proof assistants as an external aid tool to save user effort. For this it is crucial that Leo-II returns proof information in a standardised syntax, so that these proofs can eventually be transformed and verified within proof assistants. Recent progress in this direction is reported for the Isabelle/HOL system.

G\"odel's ontological proof has been analysed for the first-time with an unprecedent degree of detail and formality with the help of higher-order theorem provers. The following has been done (and in this order): A detailed natural deduction proof. A formalization of the axioms, definitions and theorems in the TPTP THF syntax. Automatic verification of the consistency of the axioms and definitions with Nitpick. Automatic demonstration of the theorems with the provers LEO-II and Satallax. A step-by-step formalization using the Coq proof assistant. A formalization using the Isabelle proof assistant, where the theorems (and some additional lemmata) have been automated with Sledgehammer and Metis.

When mathematicians present proofs they usually adapt their explanations to their didactic goals and to the (assumed) knowledge of their addressees. Modern automated theorem provers, in contrast, present proofs usually at a fixed level of detail (also called granularity). Often these presentations are neither intended nor suitable for human use. A challenge therefore is to develop user- and goal-adaptive proof presentation techniques that obey common mathematical practice. We present a flexible and adaptive approach to proof presentation that exploits machine learning techniques to extract a model of the specific granularity of

Abstract. In this paper we re-examine the semantics of classical higher-order logic with the purpose of clarifying the role of extensionality. To reach this goal, we distinguish nine classes of higher-order models with respect to various combinations of Boolean extensionality and three forms of functional extensionality. Furthermore, we develop a methodology of abstract consistency methods (by providing the necessary model existence theorems) needed to analyze completeness of (machine-oriented) higher-order calculi with respect to these model classes.

Abstract. The capabilities of a automated theorem prover's interface are essential for the effective use of (interactive) proof systems. L Ω UI is the multi-modal interface that combines several features: a graphical display of information in a proof graph, a selective term browser with hypertext facilities, proof and proof plan presentation in natural language, and an editor for adding and maintaining the knowledge base. L Ω UI is realized in an agent-based client-server architecture and implemented in the concurrent constraint programming language Oz.