70 citations · 114 across the 20 of their papers we have counts for
21 papers
Planning for Temporally Extended Goals in Pure-Past Linear Temporal Logic: A Polynomial Reduction to Standard Planning
Giuseppe De Giacomo, Marco Favorito, Francesco Fuggitti
We study temporally extended goals expressed in Pure-Past LTL (PPLTL). PPLTL is particularly interesting for expressing goals since it allows to express sophisticated tasks as in t…
Markov Abstractions for PAC Reinforcement Learning in Non-Markov Decision Processes
Alessandro Ronca, Gabriel Paludo Licks, Giuseppe De Giacomo
Our work aims at developing reinforcement learning algorithms that do not rely on the Markov assumption. We consider the class of Non-Markov Decision Processes where histories can…
Iterative Depth-First Search for Fully Observable Non-Deterministic Planning
Ramon Fraga Pereira, André G. Pereira, Frederico Messa +1
Fully Observable Non-Deterministic (FOND) planning models uncertainty through actions with non-deterministic effects. Existing FOND planning algorithms are effective and employ a w…
Efficient PAC Reinforcement Learning in Regular Decision Processes
Alessandro Ronca, Giuseppe De Giacomo
Recently regular decision processes have been proposed as a well-behaved form of non-Markov decision process. Regular decision processes are characterised by a transition function…
Recognizing LTLf/PLTLf Goals in Fully Observable Non-Deterministic Domain Models
Ramon Fraga Pereira, Francesco Fuggitti, Giuseppe De Giacomo
Goal Recognition is the task of discerning the correct intended goal that an agent aims to achieve, given a set of possible goals, a domain model, and a sequence of observations as…
Behavioral QLTL
Giuseppe De Giacomo, Giuseppe Perelli
In this paper we introduce Behavioral QLTL, which is a ``behavioral'' variant of linear-time temporal logic on infinite traces with second-order quantifiers. Behavioral QLTL is cha…
Stochastic Fairness and Language-Theoretic Fairness in Planning on Nondeterministic Domains
Benjamin Aminof, Giuseppe De Giacomo, Sasha Rubin
We address two central notions of fairness in the literature of planning on nondeterministic fully observable domains. The first, which we call stochastic fairness, is classical, a…
LTLf Synthesis with Fairness and Stability Assumptions
Shufang Zhu, Giuseppe De Giacomo, Geguang Pu +1
In synthesis, assumptions are constraints on the environment that rule out certain environment behaviors. A key observation here is that even if we consider systems with LTLf goals…
Generalized Planning: Non-Deterministic Abstractions and Trajectory Constraints
Blai Bonet, Giuseppe De Giacomo, Hector Geffner +1
We study the characterization and computation of general policies for families of problems that share a structure characterized by a common reduction into a single abstract problem…
Hybrid Temporal Situation Calculus
Vitaliy Batusov, Giuseppe De Giacomo, Mikhail Soutchanski
The ability to model continuous change in Reiter's temporal situation calculus action theories has attracted a lot of interest. In this paper, we propose a new development of his a…
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…
Planning and Synthesis Under Assumptions
Benjamin Aminof, Giuseppe De Giacomo, Aniello Murano +1
In Reasoning about Action and Planning, one synthesizes the agent plan by taking advantage of the assumption on how the environment works (that is, one exploits the environment's e…
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…
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…
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…
Fixpoint Node Selection Query Languages for Trees
Diego Calvanese, Giuseppe De Giacomo, Maurizio Lenzerini +1
The study of node selection query languages for (finite) trees has been a major topic in the recent research on query languages for Web documents. On one hand, there has been an ex…
LTLf and LDLf Monitoring: A Technical Report
Giuseppe De Giacomo, Riccardo De Masellis, Marco Grasso +2
Runtime monitoring is one of the central tasks to provide operational decision support to running business processes, and check on-the-fly whether they comply with constraints and…
Description Logic Knowledge and Action Bases
Babak Bagheri Hariri, Diego Calvanese, Marco Montali +3
Description logic Knowledge and Action Bases (KAB) are a mechanism for providing both a semantically rich representation of the information on the domain of interest in terms of a…
Verification of Relational Data-Centric Dynamic Systems with External Services
Babak Bagheri Hariri, Diego Calvanese, Giuseppe De Giacomo +2
Data-centric dynamic systems are systems where both the process controlling the dynamics and the manipulation of data are equally central. In this paper we study verification of (f…
View Synthesis from Schema Mappings
Diego Calvanese, Giuseppe De Giacomo, Maurizio Lenzerini +1
In data management, and in particular in data integration, data exchange, query optimization, and data privacy, the notion of view plays a central role. In several contexts, such a…
A Uniform Framework for Concept Definitions in Description Logics
G. DeGiacomo, M. Lenzerini
Most modern formalisms used in Databases and Artificial Intelligence for describing an application domain are based on the notions of class (or concept) and relationship among clas…