activity
20092026
most citedFoundations for Restraining Bolts: Reinforcement Learning with LTLf/LDLf restraining specifications

18 citations · 38 across the 14 of their papers we have counts for

collaborators

14 papers

cs.AI2026

Incremental LTLf Synthesis

Giuseppe De Giacomo, Yves Lespérance, Gianmarco Parretti +2

In this paper, we study incremental LTLf synthesis -- a form of reactive synthesis where the goals are given incrementally while in execution. In other words, the protagonist agent…

cs.LO2023★ 1 cited

Optimal Alignment of Temporal Knowledge Bases

Oliver Fernandez-Gil, Fabio Patrizi, Giuseppe Perelli +1

Answering temporal CQs over temporalized Description Logic knowledge bases (TKB) is a main technique to realize ontology-based situation recognition. In case the collected data in…

cs.LG2023★ 1 cited

Exploiting Multiple Abstractions in Episodic RL via Reward Shaping

Roberto Cipollone, Giuseppe De Giacomo, Marco Favorito +2

One major limitation to the applicability of Reinforcement Learning (RL) to many practical domains is the large number of samples required to learn an optimal policy. To address th…

cs.LO2022★ 2 cited

Monitoring Arithmetic Temporal Properties on Finite Traces

Paolo Felli, Marco Montali, Fabio Patrizi +1

We study monitoring of linear-time arithmetic properties against finite traces generated by an unknown dynamic system. The monitoring state is determined by considering at once the…

cs.AI2022★ 1 cited

Mimicking Behaviors in Separated Domains

Giuseppe De Giacomo, Dror Fried, Fabio Patrizi +1

Devising a strategy to make a system mimicking behaviors from another system is a problem that naturally arises in many areas of Computer Science. In this work, we interpret this p…

cs.AI2022

ASP-Based Declarative Process Mining (Extended Abstract)

Francesco Chiariello, Fabrizio Maria Maggi, Fabio Patrizi

We propose Answer Set Programming (ASP) as an approach for modeling and solving problems from the area of Declarative Process Mining (DPM). We consider here three classical problem…

cs.AI2021

Monitoring Hybrid Process Specifications with Conflict Management: The Automata-theoretic Approach

Anti Alman, Fabrizio Maria Maggi, Marco Montali +2

Business process monitoring approaches have thus far mainly focused on monitoring the execution of a process with respect to a single process model. However, in some cases it is ne…

cs.DB2018★ 1 cited

Modeling and In-Database Management of Relational, Data-Aware Processes (Extended Version)

Diego Calvanese, Marco Montali, Fabio Patrizi +1

During the last two decades, it has been increasingly acknowledged that the engineering of information systems usually requires a huge effort in integrating master data and busines…

cs.AI2018★ 1 cited

Situation Calculus for Synthesis of Manufacturing Controllers

Giuseppe De Giacomo, Brian Logan, Paolo Felli +2

Manufacturing is transitioning from a mass production model to a manufacturing as a service model in which manufacturing facilities 'bid' to produce products. To decide whether to…

cs.LG2018★ 18 cited

Foundations for Restraining Bolts: Reinforcement Learning with LTLf/LDLf restraining specifications

Giuseppe De Giacomo, Luca Iocchi, Marco Favorito +1

In this work we investigate on the concept of "restraining bolt", envisioned in Science Fiction. Specifically we introduce a novel problem in AI. We have two distinct sets of featu…

cs.AI2017★ 2 cited

Specifying Non-Markovian Rewards in MDPs Using LDL on Finite Traces (Preliminary Version)

Ronen Brafman, Giuseppe De Giacomo, Fabio Patrizi

In Markov Decision Processes (MDPs), the reward obtained in a state depends on the properties of the last state and action. This state dependency makes it difficult to reward more…

cs.AI2015

Bounded Situation Calculus Action Theories

Giuseppe De Giacomo, Yves Lespérance, Fabio Patrizi

In this paper, we investigate bounded action theories in the situation calculus. A bounded action theory is one which entails that, in every situation, the number of object tuples…

cs.MA2013★ 4 cited

Verification of Agent-Based Artifact Systems

Francesco Belardinelli, Alessio Lomuscio, Fabio Patrizi

Artifact systems are a novel paradigm for specifying and implementing business processes described in terms of interacting modules called artifacts. Artifacts consist of data and l…

cs.SE2009★ 7 cited

An Introduction to Simulation-Based Techniques for Automated Service Composition

Fabio Patrizi

This work is an introduction to the author's contributions to the SOC area, resulting from his PhD research activity. It focuses on the problem of automatically composing a desired…