no code implementations • 4 Jan 2024 • Vishal Pallagani, Kaushik Roy, Bharath Muppasani, Francesco Fabiano, Andrea Loreggia, Keerthiram Murugesan, Biplav Srivastava, Francesca Rossi, Lior Horesh, Amit Sheth
Automated Planning and Scheduling is among the growing areas in Artificial Intelligence (AI) where mention of LLMs has gained popularity.
no code implementations • 4 Aug 2023 • Thiago Dal Pont, Federico Galli, Andrea Loreggia, Giuseppe Pisano, Riccardo Rovatti, Giovanni Sartor
We present some initial results of a large-scale Italian project called PRODIGIT which aims to support tax judges and lawyers through digital technology, focusing on AI.
no code implementations • 14 Jul 2023 • Marianna B. Ganapini, Francesco Fabiano, Lior Horesh, Andrea Loreggia, Nicholas Mattei, Keerthiram Murugesan, Vishal Pallagani, Francesca Rossi, Biplav Srivastava, Brent Venable
Values that are relevant to a specific decision scenario are used to decide when and how to use each of these nudging modalities.
no code implementations • 25 May 2023 • Vishal Pallagani, Bharath Muppasani, Keerthiram Murugesan, Francesca Rossi, Biplav Srivastava, Lior Horesh, Francesco Fabiano, Andrea Loreggia
Firstly, we want to understand the extent to which LLMs can be used for plan generation.
no code implementations • 7 Mar 2023 • Francesco Fabiano, Vishal Pallagani, Marianna Bergamaschi Ganapini, Lior Horesh, Andrea Loreggia, Keerthiram Murugesan, Francesca Rossi, Biplav Srivastava
The concept of Artificial Intelligence has gained a lot of attention over the last decade.
no code implementations • 16 Dec 2022 • Vishal Pallagani, Bharath Muppasani, Keerthiram Murugesan, Francesca Rossi, Lior Horesh, Biplav Srivastava, Francesco Fabiano, Andrea Loreggia
Large Language Models (LLMs) have been the subject of active research, significantly advancing the field of Natural Language Processing (NLP).
no code implementations • 21 Feb 2022 • Arie Glazier, Andrea Loreggia, Nicholas Mattei, Taher Rahgooy, Francesca Rossi, Brent Venable
Many real-life scenarios require humans to make difficult trade-offs: do we always follow all the traffic rules or do we violate the speed limit in an emergency?
no code implementations • 19 Jan 2022 • Edmond Awad, Sydney Levine, Andrea Loreggia, Nicholas Mattei, Iyad Rahwan, Francesca Rossi, Kartik Talamadupula, Joshua Tenenbaum, Max Kleiman-Weiner
We can invent novel rules on the fly.
no code implementations • 18 Jan 2022 • Marianna B. Ganapini, Murray Campbell, Francesco Fabiano, Lior Horesh, Jon Lenchner, Andrea Loreggia, Nicholas Mattei, Taher Rahgooy, Francesca Rossi, Biplav Srivastava, Brent Venable
Current AI systems lack several important human capabilities, such as adaptability, generalizability, self-control, consistency, common sense, and causal reasoning.
no code implementations • 24 Dec 2021 • Loris Nanni, Daniela Cuza, Alessandra Lumini, Andrea Loreggia, Sheryl Brahnam
Semantic segmentation consists in classifying each pixel of an image by assigning it to a specific label chosen from a set of all the available ones.
no code implementations • 5 Oct 2021 • Marianna Bergamaschi Ganapini, Murray Campbell, Francesco Fabiano, Lior Horesh, Jon Lenchner, Andrea Loreggia, Nicholas Mattei, Francesca Rossi, Biplav Srivastava, Kristen Brent Venable
AI systems have seen dramatic advancement in recent years, bringing many applications that pervade our everyday life.
no code implementations • 22 Sep 2021 • Arie Glazier, Andrea Loreggia, Nicholas Mattei, Taher Rahgooy, Francesca Rossi, K. Brent Venable
To this end, we propose a novel inverse reinforcement learning (IRL) method for learning implicit hard and soft constraints from demonstrations, enabling agents to quickly adapt to new settings.
1 code implementation • 16 Sep 2021 • Andrea Loreggia, Simone Mosco, Alberto Zerbinati
In this work, we present SenTag, a lightweight web-based tool focused on semantic annotation of textual documents.
no code implementations • 9 Apr 2021 • Andrea Loreggia, Anna Passarelli, Maria Silvia Pini
The COVID-19 pandemic considerably affects public health systems around the world.
no code implementations • 12 Oct 2020 • Grady Booch, Francesco Fabiano, Lior Horesh, Kiran Kate, Jon Lenchner, Nick Linck, Andrea Loreggia, Keerthiram Murugesan, Nicholas Mattei, Francesca Rossi, Biplav Srivastava
This paper proposes a research direction to advance AI which draws inspiration from cognitive theories of human decision making.
no code implementations • 23 Mar 2020 • Roberta Calegari, Andrea Loreggia, Emiliano Lorini, Francesca Rossi, Giovanni Sartor
In a ceteris-paribus semantics for deontic logic, a state of affairs where a larger set of prescriptions is respected is preferable to a state of affairs where some of them are violated.
no code implementations • 18 Sep 2019 • Cristina Cornelio, Michele Donini, Andrea Loreggia, Maria Silvia Pini, Francesca Rossi
In many machine learning scenarios, looking for the best classifier that fits a particular dataset can be very costly in terms of time and resources.
no code implementations • 21 Sep 2018 • Andrea Loreggia, Nicholas Mattei, Francesca Rossi, K. Brent Venable
CPDist is a novel metric learning approach based on the use of deep siamese networks which learn the Kendal Tau distance between partial orders that are induced by compact preference representations.
no code implementations • 24 Apr 2015 • Cristina Cornelio, Andrea Loreggia, Vijay Saraswat
CP-nets represent the dominant existing framework for expressing qualitative conditional preferences between alternatives, and are used in a variety of areas including constraint solving.