arXiv subjects

André Platzer

Publications and source records attributed to André Platzer.

At least 37 records · Page 2Linked to original sources

arXiv2025

A Real-Analytic Approach to Differential-Algebraic Dynamic Logic

This paper introduces a proof calculus for real-analytic differential-algebraic dynamic logic, enabling correct transformations of differential-algebraic equations. Applications include index reductions from differential-algebraic equations to ordinary differential equations. The calculus ensures compatibility between differential-algebraic equation proof principles and (differential-form) differential dynamic logic for hybrid systems. One key contribution is ghost switching which establishes precise conditions that decompose multi-modal systems into hybrid systems, thereby correctly hybridizing sophisticated differential-algebraic dynamics. The calculus is demonstrated in a proof of equivalence for a Euclidean pendulum to index reduced form.

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arXiv2025

Verification of Autonomous Neural Car Control with KeYmaera X

This article presents a formal model and formal safety proofs for the ABZ'25 case study in differential dynamic logic (dL). The case study considers an autonomous car driving on a highway avoiding collisions with neighbouring cars. Using KeYmaera X's dL implementation, we prove absence of collision on an infinite time horizon which ensures that safety is preserved independently of trip length. The safety guarantees hold for time-varying reaction time and brake force. Our dL model considers the single lane scenario with cars ahead or behind. We demonstrate that dL with its tools is a rigorous foundation for runtime monitoring, shielding, and neural network verification. Doing so sheds light on inconsistencies between the provided specification and simulation environment highway-env of the ABZ'25 study. We attempt to fix these inconsistencies and uncover numerous counterexamples which also indicate issues in the provided reinforcement learning environment.

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arXiv2025

Adaptive Shielding via Parametric Safety Proofs

A major challenge to deploying cyber-physical systems with learning-enabled controllers is to ensure their safety, especially in the face of changing environments that necessitate runtime knowledge acquisition. Model-checking and automated reasoning have been successfully used for shielding, i.e., to monitor untrusted controllers and override potentially unsafe decisions, but only at the cost of hard tradeoffs in terms of expressivity, safety, adaptivity, precision and runtime efficiency. We propose a programming-language framework that allows experts to statically specify adaptive shields for learning-enabled agents, which enforce a safe control envelope that gets more permissive as knowledge is gathered at runtime. A shield specification provides a safety model that is parametric in the current agent's knowledge. In addition, a nondeterministic inference strategy can be specified using a dedicated domain-specific language, enforcing that such knowledge parameters are inferred at runtime in a statistically-sound way. By leveraging language design and theorem proving, our proposed framework empowers experts to design adaptive shields with an unprecedented level of modeling flexibility, while providing rigorous, end-to-end probabilistic safety guarantees.

cs.PL↗

arXiv2024

Provably Safe Neural Network Controllers via Differential Dynamic Logic

While neural networks (NNs) have potential as autonomous controllers for Cyber-Physical Systems, verifying the safety of NN based control systems (NNCSs) poses significant challenges for the practical use of NNs, especially when safety is needed for unbounded time horizons. One reason is the intractability of analyzing NNs, ODEs and hybrid systems. To this end, we introduce VerSAILLE (Verifiably Safe AI via Logically Linked Envelopes): The first general approach that allows reusing control theory results for NNCS verification. By joining forces, we exploit the efficiency of NN verification tools while retaining the rigor of differential dynamic logic (dL). Based on provably safe control envelopes in dL, we derive specifications for the NN which is proven via NN verification. We show that a proof of the NN adhering to the specification is mirrored by a dL proof on the infinite-time safety of the NNCS. The NN verification properties resulting from hybrid systems typically contain nonlinear arithmetic and arbitrary logical structures while efficient NN verification merely supports linear constraints. To overcome this divide, we present Mosaic: An efficient, sound and complete verification approach for polynomial real arithmetic properties on piece-wise linear NNs. Mosaic partitions complex verification queries into simple queries and lifts off-the-shelf linear constraint tools to the nonlinear setting in a completeness-preserving manner by combining approximation with exact reasoning for counterexample regions. Our evaluation demonstrates the versatility of VerSAILLE and Mosaic: We prove infinite-time safety on the classical Vertical Airborne Collision Avoidance NNCS verification benchmark for two scenarios while (exhaustively) enumerating counterexample regions in unsafe scenarios. We also show that our approach significantly outperforms State-of-the-Art tools in closed-loop NNV.

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arXiv2024

Axiomatization of Compact Initial Value Problems: Open Properties

This article proves the completeness of an axiomatization for initial value problems (IVPs) with compact initial conditions and compact time horizons for bounded open safety, open liveness and existence properties. Completeness systematically reduces the proofs of these properties to a complete axiomatization for differential equation invariants. This result unifies symbolic logic and numerical analysis by a computable procedure that generates symbolic proofs with differential invariants for rigorous error bounds of numerical solutions to polynomial initial value problems. The procedure is modular and works for all polynomial IVPs with rational coefficients and initial conditions and symbolic parameters constrained to compact sets. Furthermore, this paper discusses generalizations to IVPs with initial conditions/symbolic parameters that are not necessarily constrained to compact sets, achieved through the derivation of fully symbolic axioms/proof-rules based on the axiomatization.

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arXiv2024

A Usage-Aware Sequent Calculus for Differential Dynamic Logic

Ensuring that safety-critical applications behave as intended is an important yet challenging task. Modeling languages like differential dynamic logic (dL) have proof calculi capable of proving guarantees for such applications. However, dL programmers may unintentionally over-specify assumptions and program statements, which results in overly constrained models that yield weak or vacuous guarantees. In hybrid systems models, such constraints are ubiquitous; they may appear as assumptions, conditions on control switches, and evolution domain constraints in systems of differential equations which makes it nontrivial to systematically detect which ones are over-specified. Existing approaches are limited, either lacking formal correctness guarantees or the granularity to detect all kinds of bugs arising in a given formula. As a remedy, we present a novel proof-based technique that detects which constraints in a dL formula are vacuous or over-specified and suggests ways in which these components could be mutated while preserving correctness proofs. When properties follow entirely from constraints uninfluenced by program statements, this analysis spots outright flaws in models. Otherwise, it helps make models more flexible by identifying specific ways in which they may be generalized. The resulting analysis is thorough, catching bugs at a fine-grained level and proposing mutations that could be applied in combination. We prove soundness and completeness with respect to dL to ensure the correctness of suggested mutations and general applicability of our technique.

cs.FL↗

arXiv2024

Intersymbolic AI: Interlinking Symbolic AI and Subsymbolic AI

This perspective piece calls for the study of the new field of Intersymbolic AI, by which we mean the combination of symbolic AI, whose building blocks have inherent significance/meaning, with subsymbolic AI, whose entirety creates significance/effect despite the fact that individual building blocks escape meaning. Canonical kinds of symbolic AI are logic, games and planning. Canonical kinds of subsymbolic AI are (un)supervised machine and reinforcement learning. Intersymbolic AI interlinks the worlds of symbolic AI with its compositional symbolic significance and meaning and of subsymbolic AI with its summative significance or effect to enable culminations of insights from both worlds by going between and across symbolic AI insights with subsymbolic AI techniques that are being helped by symbolic AI principles. For example, Intersymbolic AI may start with symbolic AI to understand a dynamic system, continue with subsymbolic AI to learn its control, and end with symbolic AI to safely use the outcome of the learned subsymbolic AI controller in the dynamic system. The way Intersymbolic AI combines both symbolic and subsymbolic AI to increase the effectiveness of AI compared to either kind of AI alone is likened to the way that the combination of both conscious and subconscious thought increases the effectiveness of human thought compared to either kind of thought alone. Some successful contributions to the Intersymbolic AI paradigm are surveyed here but many more are considered possible by advancing Intersymbolic AI.

cs.AI↗

arXiv2024

The Significance of Symbolic Logic for Scientific Education

This invited paper is a passionate pitch for the significance of logic in scientific education. Logic helps focus on the essential core to identify the foundations of ideas and provides corresponding longevity with the resulting approach to new and old problems. Logic operates symbolically, where each part has a precise meaning and the meaning of the whole is compositional, so a simple function of the meaning of the pieces. This compositionality in the meaning of logical operators is the basis for compositionality in reasoning about logical operators. Both semantic and deductive compositionalities help explain what happens in reasoning. The correctness-critical core of an idea or an algorithm is often expressible eloquently and particularly concisely in logic. The opinions voiced in this paper are influenced by the author's teaching of courses on cyber-physical systems, constructive logic, compiler design, programming language semantics, and imperative programming principles. In each of those courses, different aspects of logic come up for different purposes to elucidate significant ideas particularly clearly. While there is a bias of the thoughts in this paper toward computer science, some courses have been heavily frequented by students from other majors so that some transfer of the thoughts to other science and engineering disciplines is plausible.

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arXiv2024

Complete Game Logic with Sabotage

Game Logic with sabotage ($\mathsf{GL_s}$) is introduced as a simple and natural extension of Parikh's game logic with a single additional primitive, which allows players to lay traps for the opponent. $\mathsf{GL_s}$ can be used to model infinite sabotage games, in which players can change the rules during game play. In contrast to game logic, which is strictly less expressive, $\mathsf{GL_s}$ is exactly as expressive as the modal $μ$-calculus. This reveals a close connection between the entangled nested recursion inherent in modal fixpoint logics and adversarial dynamic rule changes characteristic for sabotage games. A natural Hilbert-style proof calculus for $\mathsf{GL_s}$ is presented and proved complete using syntactic equiexpressiveness reductions. The completeness of a simple extension of Parikh's calculus for game logic follows.

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arXiv2024

Uniform Substitution for Differential Refinement Logic

This paper introduces a uniform substitution calculus for differential refinement logic dRL. The logic dRL extends the differential dynamic logic dL such that one can simultaneously reason about properties of and relations between hybrid systems. Refinements are useful e.g. for simplifying proofs by relating a concrete hybrid system to an abstract one from which the property can be proved more easily. Uniform substitution is the key to parsimonious prover microkernels. It enables the verbatim use of single axiom formulas instead of axiom schemata with soundness-critical side conditions scattered across the proof calculus. The uniform substitution rule can then be used to instantiate all axioms soundly. Access to differential variables in dRL enables more control over the notion of refinement, which is shown to be decidable on a fragment of hybrid programs.

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arXiv2024

CESAR: Control Envelope Synthesis via Angelic Refinements

This paper presents an approach for synthesizing provably correct control envelopes for hybrid systems. Control envelopes characterize families of safe controllers and are used to monitor untrusted controllers at runtime. Our algorithm fills in the blanks of a hybrid system's sketch specifying the desired shape of the control envelope, the possible control actions, and the system's differential equations. In order to maximize the flexibility of the control envelope, the synthesized conditions saying which control action can be chosen when should be as permissive as possible while establishing a desired safety condition from the available assumptions, which are augmented if needed. An implicit, optimal solution to this synthesis problem is characterized using hybrid systems game theory, from which explicit solutions can be derived via symbolic execution and sound, systematic game refinements. Optimality can be recovered in the face of approximation via a dual game characterization. The resulting algorithm, Control Envelope Synthesis via Angelic Refinements (CESAR), is demonstrated in a range of safe control synthesis examples with different control challenges.

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arXiv2023

Uniform Substitution for Dynamic Logic with Communicating Hybrid Programs

This paper introduces a uniform substitution calculus for $\mathsf{dL}_\text{CHP}$, the dynamic logic of communicating hybrid programs. Uniform substitution enables parsimonious prover kernels by using axioms instead of axiom schemata. Instantiations can be recovered from a single proof rule responsible for soundness-critical instantiation checks rather than being spread across axiom schemata in side conditions. Even though communication and parallelism reasoning are notorious for necessitating subtle soundness-critical side conditions, uniform substitution when generalized to $\mathsf{dL}_\text{CHP}$ manages to limit and isolate their conceptual overhead. Since uniform substitution has proven to simplify the implementation of hybrid systems provers substantially, uniform substitution for $\mathsf{dL}_\text{CHP}$ paves the way for a parsimonious implementation of theorem provers for hybrid systems with communication and parallelism.

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arXiv2023

Dynamic Logic of Communicating Hybrid Programs

This paper presents a dynamic logic $d\mathcal{L}_\text{CHP}$ for compositional deductive verification of communicating hybrid programs (CHPs). CHPs go beyond the traditional mixed discrete and continuous dynamics of hybrid systems by adding CSP-style operators for communication and parallelism. A compositional proof calculus is presented that modularly verifies CHPs including their parallel compositions from proofs of their subprograms by assumption-commitment reasoning in dynamic logic. Unlike Hoare-style assumption-commitments, $d\mathcal{L}_\text{CHP}$ supports intuitive symbolic execution via explicit recorder variables for communication primitives. Since $d\mathcal{L}_\text{CHP}$ is a conservative extension of differential dynamic logic $d\mathcal{L}$, it can be used soundly along with the $d\mathcal{L}$ proof calculus and $d\mathcal{L}$'s complete axiomatization for differential equation invariants.

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arXiv2022

A First Complete Algorithm for Real Quantifier Elimination in Isabelle/HOL

We formalize a multivariate quantifier elimination (QE) algorithm in the theorem prover Isabelle/HOL. Our algorithm is complete, in that it is able to reduce any quantified formula in the first-order logic of real arithmetic to a logically equivalent quantifier-free formula. The algorithm we formalize is a hybrid mixture of Tarski's original QE algorithm and the Ben-Or, Kozen, and Reif algorithm, and it is the first complete multivariate QE algorithm formalized in Isabelle/HOL.

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arXiv2022

Learning to Find Proofs and Theorems by Learning to Refine Search Strategies: The Case of Loop Invariant Synthesis

We propose a new approach to automated theorem proving where an AlphaZero-style agent is self-training to refine a generic high-level expert strategy expressed as a nondeterministic program. An analogous teacher agent is self-training to generate tasks of suitable relevance and difficulty for the learner. This allows leveraging minimal amounts of domain knowledge to tackle problems for which training data is unavailable or hard to synthesize. As a specific illustration, we consider loop invariant synthesis for imperative programs and use neural networks to refine both the teacher and solver strategies.

cs.AI↗

arXiv2022

Implicit Definitions with Differential Equations for KeYmaera X (System Description)

Definition packages in theorem provers provide users with means of defining and organizing concepts of interest. This system description presents a new definition package for the hybrid systems theorem prover KeYmaera X based on differential dynamic logic (dL). The package adds KeYmaera X support for user-defined smooth functions whose graphs can be implicitly characterized by dL formulas. Notably, this makes it possible to implicitly characterize functions, such as the exponential and trigonometric functions, as solutions of differential equations and then prove properties of those functions using dL's differential equation reasoning principles. Trustworthiness of the package is achieved by minimally extending KeYmaera X's soundness-critical kernel with a single axiom scheme that expands function occurrences with their implicit characterization. Users are provided with a high-level interface for defining functions and non-soundness-critical tactics that automate low-level reasoning over implicit characterizations in hybrid system proofs.

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arXiv2022

Verifying Switched System Stability With Logic

Switched systems are known to exhibit subtle (in)stability behaviors requiring system designers to carefully analyze the stability of closed-loop systems that arise from their proposed switching control laws. This paper presents a formal approach for verifying switched system stability that blends classical ideas from the controls and verification literature using differential dynamic logic (dL), a logic for deductive verification of hybrid systems. From controls, we use standard stability notions for various classes of switching mechanisms and their corresponding Lyapunov function-based analysis techniques. From verification, we use dL's ability to verify quantified properties of hybrid systems and dL models of switched systems as looping hybrid programs whose stability can be formally specified and proven by finding appropriate loop invariants, i.e., properties that are preserved across each loop iteration. This blend of ideas enables a trustworthy implementation of switched system stability verification in the KeYmaera X prover based on dL. For standard classes of switching mechanisms, the implementation provides fully automated stability proofs, including searching for suitable Lyapunov functions. Moreover, the generality of the deductive approach also enables verification of switching control laws that require non-standard stability arguments through the design of loop invariants that suitably express specific intuitions behind those control laws. This flexibility is demonstrated on three case studies: a model for longitudinal flight control by Branicky, an automatic cruise controller, and Brockett's nonholonomic integrator.

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arXiv2022

Formally Verified Next-Generation Airborne Collision Avoidance Games in ACAS X

The design of aircraft collision avoidance algorithms is a subtle but important challenge that merits the need for provable safety guarantees. Obtaining such guarantees is nontrivial given the unpredictability of the interplay of the intruder aircraft decisions, the ownship pilot reactions, and the subtlety of the continuous motion dynamics of aircraft. Existing collision avoidance systems, such as TCAS and the Next-Generation Airborne Collision Avoidance System ACAS X, have been analyzed assuming severe restrictions on the intruder's flight maneuvers, limiting their safety guarantees in real-world scenarios where the intruder may change its course. This work takes a conceptually significant and practically relevant departure from existing ACAS X models by generalizing them to hybrid games with first-class representations of the ownship and intruder decisions coming from two independent players, enabling significantly advanced predictive power. By proving the existence of winning strategies for the resulting Adversarial ACAS X in differential game logic, collision-freedom is established for the rich encounters of ownship and intruder aircraft with independent decisions along differential equations for flight paths with evolving vertical/horizontal velocities. We present three classes of models of increasing complexity: single-advisory infinite-time models, bounded time models, and infinite time, multi-advisory models. Within each class of models, we identify symbolic conditions and prove that there then always is a possible ownship maneuver that will prevent a collision between the two aircraft.

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