Giuseppe Primiero

OVERLAY Workshop 2025 Workshop Paper

A Proof System with Causal Labels (Part I): checking Individual Fairness and Intersectionality

• Leonardo Ceragioli
• Giuseppe Primiero

OVERLAY Workshop 2025 Workshop Paper

A Proof System with Causal Labels (Part II): checking Counterfactual Fairness

• Leonardo Ceragioli
• Giuseppe Primiero

EUMAS Conference 2025 Conference Paper

Ethical Decision-Making for Trustworthy Autonomous Systems under Uncertainty

• Alison Bifolco
• Louise A. Dennis
• Giuseppe Primiero

FLAP Journal 2021 Journal Article

HTLC: Hyperintensional Typed Lambda Calculus.

• Michal Fait
• Giuseppe Primiero

In this paper we introduce the logic HTLC, for Hyperintensional Typed Lambda Calculus. The system extends the typed λ-calculus with hyperintensions and related rules. The polymorphic nature of the system allows to reason with expressions for extensional, intensional and hyperintentsional entities. We inspect meta-theoretical properties and show that HTLC is complete in Henkin’s sense under a weakening of the cardinality constraint for the domain of hyperintensions.

KR Conference 2021 Short Paper

Introducing k-lingo: a k-depth Bounded Version of ASP System Clingo

• Fabio Aurelio D'Asaro
• Paolo Baldi
• Giuseppe Primiero

Depth-Bounded Boolean Logics (DBBL for short) are well-understood frameworks to model rational agents equipped with limited deductive capabilities. These Logics use a parameter k>=0 to limit the amount of virtual information, i. e. , the information that the agent may temporarily assume throughout the deductive process. This restriction brings several advantageous properties over classical Propositional Logic, including polynomial decision procedures for deducibility and refutability. Inspired by DBBL, we propose a limited-depth version of the popular ASP system \clingo, tentatively dubbed k-lingo after the bound k on virtual information. We illustrate the connection between DBBL and ASP through examples involving both proof-theoretical and implementative aspects. The paper concludes with some comments on future work, which include a computational complexity characterization of the system, applications to multi-agent systems and feasible approximations of probability functions.

EUMAS Conference 2021 Conference Paper

Logic and Model Checking by Imprecise Probabilistic Interpreted Systems

• Alberto Termine
• Alessandro Antonucci 0001
• Giuseppe Primiero
• Alessandro Facchini

Abstract Stochastic multi-agent systems raise the necessity to extend probabilistic model checking to the epistemic domain. Results in this direction have been achieved by epistemic extensions of Probabilistic Computation Tree Logic and related Probabilistic Interpreted Systems. The latter, however, suffer of an important limitation: they require the probabilities governing the system’s behaviour to be fully specified. A promising way to overcome this limitation is represented by imprecise probabilities. In this paper we introduce imprecise probabilistic interpreted systems and present a related logical language and model-checking procedures based on recent advances in the study of imprecise Markov processes.

LORI Conference 2021 Conference Paper

Modelling Accuracy and Trustworthiness of Explaining Agents

• Alberto Termine
• Giuseppe Primiero
• Fabio Aurelio D'Asaro

Abstract Current research in Explainable AI includes post-hoc explanation methods that focus on building transparent explaining agents able to emulate opaque ones. Such agents are naturally required to be accurate and trustworthy. However, what it means for an explaining agent to be accurate and trustworthy is far from being clear. We characterize accuracy and trustworthiness as measures of the distance between the formal properties of a given opaque system and those of its transparent explanantes. To this aim, we extend Probabilistic Computation Tree Logic with operators to specify degrees of accuracy and trustworthiness of explaining agents. We also provide a semantics for this logic, based on a multi-agent structure and relative model-checking algorithms. The paper concludes with a simple example of a possible application.