Marcos Cramer

AI
h-index1
8papers
44citations
Novelty40%
AI Score37

8 Papers

10.6AIApr 23
Satisfying Rationality Postulates of Structured Argumentation Through Deductive Support -- Technical Report

Marcos Cramer, Tom Friese

ASPIC-style structured argumentation frameworks provide a formal basis for reasoning in artificial intelligence by combining internal argument structure with abstract argumentation semantics. A key challenge in these frameworks is ensuring compliance with five critical rationality postulates: closure, direct consistency, indirect consistency, non-interference, and crash-resistance. Recent approaches, including ASPIC$^{\ominus}$ and Deductive ASPIC$-$, have made significant progress but fall short of meeting all postulates simultaneously under a credulous semantics (e.g. preferred) in the presence of undercuts. This paper introduces Deductive ASPIC$^{\ominus}$, a novel framework that integrates gen-rebuttals from ASPIC$^{\ominus}$ with the Joint Support Bipolar Argumentation Frameworks (JSBAFs) of Deductive ASPIC$-$, incorporating preferences. We show that Deductive ASPIC$^{\ominus}$ satisfies all five rationality postulates under a version of preferred semantics. This work opens new avenues for further research on robust and logically sound structured argumentation systems.

SEFeb 11, 2025
Verifying LLM-Generated Code in the Context of Software Verification with Ada/SPARK

Marcos Cramer, Lucian McIntyre

Large language models (LLMs) have demonstrated remarkable code generation capabilities, but the correctness of the generated code cannot be inherently trusted. This paper explores the feasibility of using formal software verification, specifically the SPARK framework for Ada, to ensure the reliability of LLM-generated code. We present Marmaragan, a tool that leverages an LLM in order to generate SPARK annotations for existing programs, enabling formal verification of the code. The tool is benchmarked on a curated set of SPARK programs, with annotations selectively removed to test specific capabilities. The performance of Marmaragan with GPT-4o on the benchmark is promising, with correct annotations having been generated for 50.7% of the benchmark cases. The results establish a foundation for future work on combining the power of LLMs with the reliability of formal software verification.

AIMay 7, 2020
Technical Report of "Deductive Joint Support for Rational Unrestricted Rebuttal"

Marcos Cramer, Meghna Bhadra

In ASPIC-style structured argumentation an argument can rebut another argument by attacking its conclusion. Two ways of formalizing rebuttal have been proposed: In restricted rebuttal, the attacked conclusion must have been arrived at with a defeasible rule, whereas in unrestricted rebuttal, it may have been arrived at with a strict rule, as long as at least one of the antecedents of this strict rule was already defeasible. One systematic way of choosing between various possible definitions of a framework for structured argumentation is to study what rationality postulates are satisfied by which definition, for example whether the closure postulate holds, i.e. whether the accepted conclusions are closed under strict rules. While having some benefits, the proposal to use unrestricted rebuttal faces the problem that the closure postulate only holds for the grounded semantics but fails when other argumentation semantics are applied, whereas with restricted rebuttal the closure postulate always holds. In this paper we propose that ASPIC-style argumentation can benefit from keeping track not only of the attack relation between arguments, but also the relation of deductive joint support that holds between a set of arguments and an argument that was constructed from that set using a strict rule. By taking this deductive joint support relation into account while determining the extensions, the closure postulate holds with unrestricted rebuttal under all admissibility-based semantics. We define the semantics of deductive joint support through the flattening method.

LOOct 9, 2019
A Query-Driven Decision Procedure for Distributed Autoepistemic Logic with Inductive Definitions

Diego Agustín Ambrossio, Marcos Cramer

Distributed Autoepistemic Logic with Inductive Definitions (dAEL(ID)) is a recently proposed non-monotonic logic for says-based access control. We define a query-driven decision procedure for dAEL(ID) that is implemented in the knowledge-base system IDP. The decision procedure is designed in such a way that it allows one to determine access rights while avoiding redundant information flow between principals in order to enhance security and reduce privacy concerns. Given that the decision procedure has in the worst case an exponential runtime, it is to be regarded as a proof of concept that increases our understanding of dAEL(ID), rather than being deployed for an access control system.

LOAug 29, 2019
Technical report of "The Knowledge Base Paradigm Applied to Delegation Revocation"

Marcos Cramer, Zohreh Baniasadi, Pieter Van Hertum

In ownership-based access control frameworks with the possibility of delegating permissions and administrative rights, delegation chains will form. There are different ways to treat delegation chains when revoking rights, which give rise to different revocation schemes. In this paper, we investigate the problem of delegation revocation from the perspective of the knowledge base paradigm. A knowledge base is a formal specification of domain knowledge in a rich formal language. Multiple forms of inference can be applied to this formal specification in order to solve various problems and tasks that arise in the domain. In other words, the paradigm proposes a strict separation of concerns between information and problem solving. The knowledge base that we use in this paper specifies the effects of the various revocation schemes. By applying different inferences to this knowledge base, we can solve the following tasks: to determine the state of the system after a certain delegation or revocation; to interactively simulate the progression of the system state through time; to determine whether a user has a certain permission or administrative right given a certain state of the system; to verify invariants of the system; and to determine which revocation schemes give rise to a certain specified set of desired outcomes.

AIAug 22, 2019
SCF2 -- an Argumentation Semantics for Rational Human Judgments on Argument Acceptability: Technical Report

Marcos Cramer, Leendert van der Torre

In abstract argumentation theory, many argumentation semantics have been proposed for evaluating argumentation frameworks. This paper is based on the following research question: Which semantics corresponds well to what humans consider a rational judgment on the acceptability of arguments? There are two systematic ways to approach this research question: A normative perspective is provided by the principle-based approach, in which semantics are evaluated based on their satisfaction of various normatively desirable principles. A descriptive perspective is provided by the empirical approach, in which cognitive studies are conducted to determine which semantics best predicts human judgments about arguments. In this paper, we combine both approaches to motivate a new argumentation semantics called SCF2. For this purpose, we introduce and motivate two new principles and show that no semantics from the literature satisfies both of them. We define SCF2 and prove that it satisfies both new principles. Furthermore, we discuss findings of a recent empirical cognitive study that provide additional support to SCF2.

AIFeb 27, 2019
Technical report of "Empirical Study on Human Evaluation of Complex Argumentation Frameworks"

Marcos Cramer, Mathieu Guillaume

In abstract argumentation, multiple argumentation semantics have been proposed that allow to select sets of jointly acceptable arguments from a given argumentation framework, i.e. based only on the attack relation between arguments. The existence of multiple argumentation semantics raises the question which of these semantics predicts best how humans evaluate arguments. Previous empirical cognitive studies that have tested how humans evaluate sets of arguments depending on the attack relation between them have been limited to a small set of very simple argumentation frameworks, so that some semantics studied in the literature could not be meaningfully distinguished by these studies. In this paper we report on an empirical cognitive study that overcomes these limitations by taking into consideration twelve argumentation frameworks of three to eight arguments each. These argumentation frameworks were mostly more complex than the argumentation frameworks considered in previous studies. All twelve argumentation framework were systematically instantiated with natural language arguments based on a certain fictional scenario, and participants were shown both the natural language arguments and a graphical depiction of the attack relation between them. Our data shows that grounded and CF2 semantics were the best predictors of human argument evaluation. A detailed analysis revealed that part of the participants chose a cognitively simpler strategy that is predicted very well by grounded semantics, while another part of the participants chose a cognitively more demanding strategy that is mostly predicted well by CF2 semantics.

LOMay 7, 2014
Modelling Delegation and Revocation Schemes in IDP

Marcos Cramer, Pieter Van Hertum, Diego Agustin Ambrossio et al.

In ownership-based access control frameworks with the possibility of delegating permissions and administrative rights, chains of delegated accesses will form. There are different ways to treat these delegation chains when revoking rights, which give rise to different revocation schemes. In this paper, we show how IDP - a knowledge base system that integrates technology from ASP, SAT and CP - can be used to efficiently implement executable revocation schemes for an ownership-based access control system based on a declarative specification of their properties.