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4th Italian Workshop on Explainable Artificial Intelligence, XAI.it 2023

作者： Borzillo, Caterina Ragno, Alessio Capobianco, Roberto Department of Computer Control and Management Engineering Sapienza University of Rome RM Rome00185 Italy Sony AI

Deep reinforcement learning (DRL) models have shown great promise in various applications, but their practical adoption in critical domains is limited due to their opaque decision-making processes. To address this challenge, explainable AI (XAI) techniques aim to enhance transparency and interpretability of black-box models. However, most current interpretable systems focus on supervised learning problems, leaving reinforcement learning relatively unexplored. This paper extends the work of PW-Net, an interpretable wrapper model for DRL agents inspired by image classification methodologies. We introduce Shared-PW-Net, an interpretable deep learning model that features a fully trainable prototype layer. Unlike PW-Net, Shared-PW-Net does not rely on pre-existing prototypes. Instead, it leverages the concept of ProtoPool to automatically learn general prototypes assigned to actions during training. Additionally, we propose a novel prototype initialization method that significantly improves the model's performance. Through extensive experimentation, we demonstrate that our Shared-PW-Net achieves the same reward performance as existing methods without requiring human intervention. Our model's fully trainable prototype layer, coupled with the innovative prototype initialization approach, contributes to a clearer and more interpretable decision-making process. The code for this work is publicly available for further exploration and applications. © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Reinforcement learning

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Improving Power Response of Single-controllable VSG-Based Active Distribution Network

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CSEE Journal of Power and Energy Systems 2025年第1期11卷 102-114页

作者： Shah Fahad Arman Goudarzi Pierluigi Siano Ji Xiang Department of Electrical and Computer Engineering Missouri University of Science and TechnologyUSA University of Victoria Canada Department of Management&Innovation Systems University of SalernoItaly Department of Electrical and Electronic Engineering Science University of JohannesburgJohannesburg2006South Africa National Laboratory of Industrial Control Technology College of Electrical EngineeringZhejiang UniversityHangzhou310058China

controlling an active distribution network(ADN)from a single PCC has been advantageous for improving the performance of coordinated Intermittent RESs(IRESs).Recent studies have proposed a constant PQ regulation approach at the PCC of ADNs using coordination of non-MPPT based ***,due to the intermittent nature of DGs coupled with PCC through uni-directional broadcast communication,the PCC becomes vulnerable to transient *** address this challenge,this study first presents a detailed mathematical model of an ADN from the perspective of PCC regulation to realize rigidness of PCC against ***,an H_(∞)controller is formulated and employed to achieve optimal performance against disturbances,consequently,ensuring the least oscillations during transients at ***,an eigenvalue analysis is presented to analyze convergence speed limitations of the newly derived system ***,simulation results show the proposed method offers superior performance as compared to the state-of-the-art methods.

关键词： Cooperative control of DGs hierarchical control system high penetration of intermittent RESs H_(∞)control optimal control in power systems single-controllable active distribution networks

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A Fault-Tolerant Task Allocation Framework for Overactuated Multi-Robot Systems 9

A Fault-Tolerant Task Allocation Framework for Overactuated ...

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9th International Conference on control, Decision and Information Technologies, CoDIT 2023

作者： Govoni, Lorenzo Cristofaro, Andrea Sapienza University of Rome Department of Computer Control and Management Engineering Via Ariosto 25 Rome00185 Italy

ISBN: (纸本)9798350311402

Given a system of overactuated heterogeneous robots executing several tasks, we propose an algorithm that simultaneously assigns the tasks considering the different nature of the robots, and allocates the control while satisfying the limitations on the actuators. The efficiency of the proposed method has been tested in terms of robustness with respect to faults by means of numerical simulations, analysing different scenarios. © 2023 IEEE.

关键词： Multipurpose robots

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Sustainability, emission trading system and carbon leakage: An approach based on neural networks and multicriteria analysis

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Sustainable Operations and computers 2023年第1期4卷 147-157页

作者： D'Adamo, Idiano Gastaldi, Massimo Hachem-Vermette, Caroline Olivieri, Riccardo Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy Department of Industrial and Information Engineering and Economics University of L'Aquila L'Aquila Italy Department of Building Civil & Environmental Engineering Concordia University Montreal Canada Sapienza University of Rome Rome Italy

Two transitions, green and digital, are changing the operations and strategies of industrial systems. At the same time, businesses are challenged to be globally competitive. Europe has a very ambitious agenda as it aims to be the first climate-neutral continent in 2050. The european emissions trading scheme (EU ETS) has proven to have facilitated the reduction of significant amounts of greenhouse gas emissions, but the risk of carbon leakage is present. This work seeks to explore these issues and their relationships. Through the use of a long short-term memory (LSTM) neural network, a model is built to determine the price of european union allowance (EUA) as a function of different financial energy futures. The results show that the model is very robust and the EUA tends to vary between 78 and 91 €/tCO2. In addition, a multi-criteria decision analysis (MCDA) is applied to identify the best policy alternatives to enable businesses subject to the EU ETS to be competitive in global markets. The analysis is carried out with the help of academic and industrial experts and it emerges that the criteria considered most relevant are two: (i) public expenditure and its expected benefits and (ii) the industrial ecosystem. The policy implications identify that bonuses should be provided to businesses for innovative solutions that protect both the energy and raw material components. The framework of the 3E (Energy Efficiency, Renewable Energy, and Circular Economy) are critical to businesses' long-term strategies, flanked by digital development. © 2023 The Author(s)

关键词： Sustainable development

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Possibilities of Adopting Electric Vehicles in the Agritourism Development Context 18

Possibilities of Adopting Electric Vehicles in the Agritouri...

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18th Iberian Conference on Information Systems and Technologies, CISTI 2023

作者： Samuil, Ionela Stancioiu, Loredana Ionica, Andreea Cristina Leba, Monica University of Petrosani Department of Management and Industrial Engineering Petrosani Romania University of Petrosani Engineering and Management Doctoral School Petrosani Romania University of Petrosani Department of System Control and Computer Engineering Petrosani Romania

ISBN: (纸本)9789893347928

In a society that is looking for ways of sustainable development, the use of electric vehicles (EVs) can be an applicable solution in different fields of activity, including the tourism industry. The current research analyzes the possibility of using Buggy EVs in a predominantly agritourism region. In this sense, with the help of STELLA Architect, dynamic modeling software, a simulation is run to determine the potential behavior of tourists who use different types of off-road vehicles and their willingness to become Buggy EV users. Based on the data obtained, an algorithm is developed to size the fleet of Buggy EVs necessary for carrying out the activity, taking into account the most important characteristics of the existing Buggy EV, namely range, charging time and price. The results obtained from the study can be used as a starting point for improving the tourist experience, by integrating the technology we are so connected to. © 2023 ITMA.

关键词： computer software

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Circularity Reinforcement of Critical Raw Materials in Europe: A Case of Niobium

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Circular Economy and Sustainability 2024年第4期4卷 2449-2472页

作者： von Rennenberg, Theresa Yu, Yifei Fraccascia, Luca Yazan, Devrim Murat Department of Industrial Engineering and Business Information Systems University of Twente Drienerlolaan 5 Enschede 7522 NB Netherlands Department of Computer Control and Management Engineering Sapienza University of Rome Via Ariosto 25 Rome 00185 Italy

Critical Raw Materials attract increasing attention due to their depleting reserves and low recyclability. Niobium, one of the most rare and vital elements, is primarily found in Brazil. This research explores the potential impact of Circular Economy (CE) strategies on mitigating niobium's criticality within Europe. First, a niobium supply chain is designed and analysed by Enterprise Input–Output modelling. Second, the supply risk is calculated based on the criticality matrix proposed by the European Commission under three scenarios associated with resources, technologies, and policies. The results show that urban mining is a potential solution to reduce niobium’s criticality and mitigate its environmental impacts. A higher recycling input rate and/or a mix of recycling and substitution strategies is necessary to offset niobium’s criticality. Aligned with the CE action plan, the research offers a scientific foundation to strategically prevent the risk of niobium supply shortages. © The Author(s) 2024.

关键词： Circular economy Critical raw materials Enterprise input–output Niobium supply chain Scenario analysis

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Streamlining the New Product Introduction by Integrating the Escalation Process 18th

Streamlining the New Product Introduction by Integrating the...

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18th International Conference on Interdisciplinarity in engineering, INTER-ENG 2024

作者： Zgirdea, Mihai Ionica, Andreea Cristina Leba, Monica Engineering and Management Doctoral School University of Petrosani 20 Universitatii Petrosani332006 Romania Management and Industrial Engineering Department University of Petrosani 20 Universitatii Petrosani332006 Romania Computer and System Control Engineering Department University of Petrosani 20 Universitatii Petrosani332006 Romania

ISBN: (纸本)9783031813771

In the dynamic landscape of modern business, companies face the challenge of rapidly introducing new products to meet consumer demands. This research aims to propel NPI efficiency, focusing on the automotive industry, by enhancing cooperative effectiveness and streamlining processes. The overarch- ing objective is to expedite high-quality product with the focus of introducing a controlled escalation process to facilitate swift corrections and improvements throughout each phase of NPI. To realize these objectives, a comprehensive NPI system has been developed. Integration of an escalation process into this sys- tem enables hierarchical escalation of concerns, blocking points, and new pro- cesses, addressing common project delays. The proposed software stands out for its unique integration of the escalation process, ensuring that all organizational members are promptly informed of any deviations using a dynamic project status feature, adapting as the project progresses. The integrated escalation process not only addresses anomalies promptly but also quantifies the time taken to restore normalcy or implement corrections, thereby fostering a more responsive and effi- cient NPI framework. The paper is organized into sections comprising a literature review on NPI methodologies, the integration of an escalation process into the NPI framework, a case study illustrating the implementation of the escalation process in an existing NPI methodology, and the subsequent results. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Automotive Industry Collaborative Teamwork controlled Escalation Process Dynamic NPI Software New Product Introduction (NPI)

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LLCoach: Generating Robot Soccer Plans Using Multi-role Large Language Models

LLCoach: Generating Robot Soccer Plans Using Multi-role Larg...

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27th RoboCup International Symposium, 2024

作者： Brienza, M. Musumeci, E. Suriani, V. Affinita, D. Pennisi, A. Nardi, D. Bloisi, D.D. Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy School of Engineering University of Basilicata Potenza Italy Department of International Humanities and Social Sciences International University of Rome Rome Italy

ISBN: (纸本)9783031858581

The deployment of robots into human scenarios necessitates advanced planning strategies, particularly when we ask robots to operate in dynamic, unstructured environments. RoboCup offers the chance to deploy robots in one of those scenarios, a human-shaped game represented by a soccer match. In such scenarios, robots must operate using predefined behaviors that can fail in unpredictable conditions. This paper introduces a novel application of Large Language Models (LLMs) to address the challenge of generating actionable plans in such settings, specifically within the context of the RoboCup Standard Platform League (SPL) competitions where robots are required to autonomously execute soccer strategies that emerge from the interactions of individual agents. In particular, we propose a multi-role approach leveraging the capabilities of LLMs to generate and refine plans for a robotic soccer team. The potential of the proposed method is demonstrated through an experimental evaluation, carried out simulating multiple matches where robots with AI-generated plans play against robots running human-built code. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Anthropomorphic robots

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AI-Driven Innovations in Healthcare: Bridging Imaging and Genomics for Advanced Disease Insights

AI-Driven Innovations in Healthcare: Bridging Imaging and Ge...

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2024 Ital-IA Intelligenza Artificiale - Thematic Workshops, Ital-IA 2024

作者： Adornetto, Carlo Bruno, Pierangela Calimeri, Francesco De Rose, Edoardo Greco, Gianluigi Quarta, Alessandro Department of Mathematics and Computer Science University of Calabria Via Pietro Bucci Rende Italy Department of Computer Control and Management Engineering "Antonio Ruberti" Sapienza University of Rome Via Ariosto 25 Rome Italy

The application of Artificial Intelligence (AI) techniques for analyzing medical images and omics data is revolutionizing the healthcare industry by offering profound insights into various diseases. Achieving precise diagnoses and formulating effective treatment plans, however, demands intricate and multimodal analysis of complex, sensitive, and diverse medical datasets. Recent advancements in Machine Learning and Deep Learning have proven to be formidable in identifying and classifying specific diseases. This paper outlines the current projects undertaken by our research group in this innovative domain. © 2024 Copyright for this paper by its authors.

关键词： Adversarial machine learning

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Multi-Agent Coordination for a Partially Observable and Dynamic Robot Soccer Environment with Limited Communication 10

Multi-Agent Coordination for a Partially Observable and Dyna...

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10th Italian Workshop on Artificial Intelligence and Robotics, AIRO 2023

作者： Affinita, Daniele Volpi, Flavio Spagnoli, Valerio Suriani, Vincenzo Nardi, Daniele Bloisi, Domenico D. Department of Computer Control and Management Engineering Antonio Ruberti Sapienza University of Rome Italy Faculty of Political Science and Sociopsychological Dynamics UNINT University Rome Italy

RoboCup represents an International testbed for advancing research in AI and robotics, focusing on a definite goal: developing a robot team that can win against the human world soccer champion team by the year 2050. To achieve this goal, autonomous humanoid robots' coordination is crucial. This paper explores novel solutions within the RoboCup Standard Platform League (SPL), where a reduction in WiFi communication is imperative, leading to the development of new coordination paradigms. The SPL has experienced a substantial decrease in network packet rate, compelling the need for advanced coordination architectures to maintain optimal team functionality in dynamic environments. Inspired by market-based task assignment, we introduce a novel distributed coordination system to orchestrate autonomous robots' actions efficiently in low communication scenarios. This approach has been tested with NAO robots during official RoboCup competitions and in the SimRobot simulator, demonstrating a notable reduction in task overlaps in limited communication settings. © 2024 Copyright for this paper by its authors.

关键词： Anthropomorphic robots

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