Francesca Rossi

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Università di Padova ∙ ibm

AI ethics global leader at IBM, Professor at University of Padova

E-PDDL: A Standardized Way of Defining Epistemic Planning Problems

Epistemic Planning (EP) refers to an automated planning setting where th...
07/19/2021 ∙ by Francesco Fabiano, et al. ∙ 4 ∙ share

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Thinking Fast and Slow in AI

This paper proposes a research direction to advance AI which draws inspi...
10/12/2020 ∙ by Grady Booch, et al. ∙ 3 ∙ share

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Personalized Chatbot Trustworthiness Ratings

Conversation agents, commonly referred to as chatbots, are increasingly ...
05/13/2020 ∙ by Biplav Srivastava, et al. ∙ 0 ∙ share

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Learning and Recognizing Archeological Features from LiDAR Data

We present a remote sensing pipeline that processes LiDAR (Light Detecti...
04/05/2020 ∙ by Conrad M Albrecht, et al. ∙ 10 ∙ share

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Modeling Contrary-to-Duty with CP-nets

In a ceteris-paribus semantics for deontic logic, a state of affairs whe...
03/23/2020 ∙ by Roberta Calegari, et al. ∙ 4 ∙ share

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Voting with Random Classifiers (VORACE)

In many machine learning scenarios, looking for the best classifier that...
09/18/2019 ∙ by Cristina Cornelio, et al. ∙ 12 ∙ share

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Using deceased-donor kidneys to initiate chains of living donor kidney paired donations: algorithms and experimentation

We design a flexible algorithm that exploits deceased donor kidneys to i...
12/17/2018 ∙ by Cristina Cornelio, et al. ∙ 0 ∙ share

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Building Ethically Bounded AI

The more AI agents are deployed in scenarios with possibly unexpected si...
12/10/2018 ∙ by Francesca Rossi, et al. ∙ 8 ∙ share

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CPDist: Deep Siamese Networks for Learning Distances Between Structured Preferences

Preference are central to decision making by both machines and humans. R...
09/21/2018 ∙ by Andrea Loreggia, et al. ∙ 14 ∙ share

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Interpretable Multi-Objective Reinforcement Learning through Policy Orchestration

Autonomous cyber-physical agents and systems play an increasingly large ...
09/21/2018 ∙ by Ritesh Noothigattu, et al. ∙ 16 ∙ share

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Incorporating Behavioral Constraints in Online AI Systems

AI systems that learn through reward feedback about the actions they tak...
09/15/2018 ∙ by Avinash Balakrishnan, et al. ∙ 0 ∙ share

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Towards Composable Bias Rating of AI Services

A new wave of decision-support systems are being built today using AI se...
07/31/2018 ∙ by Biplav Srivastava, et al. ∙ 2 ∙ share

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Cognitive Hierarchy and Voting Manipulation

By the Gibbard--Satterthwaite theorem, every reasonable voting rule for ...
07/26/2017 ∙ by Edith Elkind, et al. ∙ 0 ∙ share

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Restricted Manipulation in Iterative Voting: Convergence and Condorcet Efficiency

In collective decision making, where a voting rule is used to take a col...
03/04/2013 ∙ by Umberto Grandi, et al. ∙ 0 ∙ share

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Elicitation strategies for fuzzy constraint problems with missing preferences: algorithms and experimental studies

Fuzzy constraints are a popular approach to handle preferences and over-...
09/24/2009 ∙ by Mirco Gelain, et al. ∙ 0 ∙ share

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Dealing with incomplete agents' preferences and an uncertain agenda in group decision making via sequential majority voting

We consider multi-agent systems where agents' preferences are aggregated...
09/24/2009 ∙ by Maria Pini, et al. ∙ 0 ∙ share

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Manipulation and gender neutrality in stable marriage procedures

The stable marriage problem is a well-known problem of matching men to w...
09/24/2009 ∙ by Maria Pini, et al. ∙ 0 ∙ share

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Reasoning about soft constraints and conditional preferences: complexity results and approximation techniques

Many real life optimization problems contain both hard and soft constrai...
05/22/2009 ∙ by Carmel Domshlak, et al. ∙ 0 ∙ share

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Francesca Rossi

Featured Co-authors

Toby Walsh

Djallel Bouneffouf

Nicholas Mattei

Edith Elkind

Biplav Srivastava

Lior Horesh

Murray Campbell

Michele Donini

Carmel Domshlak

Cristina Cornelio

Umberto Grandi

E-PDDL: A Standardized Way of Defining Epistemic Planning Problems

Thinking Fast and Slow in AI

Personalized Chatbot Trustworthiness Ratings

Learning and Recognizing Archeological Features from LiDAR Data

Modeling Contrary-to-Duty with CP-nets

Voting with Random Classifiers (VORACE)

Using deceased-donor kidneys to initiate chains of living donor kidney paired donations: algorithms and experimentation

Building Ethically Bounded AI

CPDist: Deep Siamese Networks for Learning Distances Between Structured Preferences

Interpretable Multi-Objective Reinforcement Learning through Policy Orchestration

Incorporating Behavioral Constraints in Online AI Systems

Towards Composable Bias Rating of AI Services

Cognitive Hierarchy and Voting Manipulation

Restricted Manipulation in Iterative Voting: Convergence and Condorcet Efficiency

Elicitation strategies for fuzzy constraint problems with missing preferences: algorithms and experimental studies

Dealing with incomplete agents' preferences and an uncertain agenda in group decision making via sequential majority voting

Manipulation and gender neutrality in stable marriage procedures

Reasoning about soft constraints and conditional preferences: complexity results and approximation techniques