Distributed argumentation technology: advancing risk analysis and regulatory compliance of distributed ledger technologies for transaction and management of securities

Distributed argumentation technology is a computational approach incorporating argumentation reasoning mechanisms within multi-agent systems. For the formal foundations of distributed argumentation technology, in this thesis we conduct a principle-based analysis of structured argumentation as well as abstract multi-agent and abstract bipolar argumentation. The results of the principle-based approach of these theories provide an overview and guideline for further applications of the theories. Moreover, in this thesis we explore distributed argumentation technology using distributed ledgers. We envision an Intelligent Human-input-based Blockchain Oracle (IHiBO), an artificial intelligence tool for storing argumentation reasoning. We propose a decentralized and secure architecture for conducting decision-making, addressing key concerns of trust, transparency, and immutability. We model fund management with agent argumentation in IHiBO and analyze its compliance with European fund management legal frameworks. We illustrate how bipolar argumentation balances pros and cons in legal reasoning in a legal divorce case, and how the strength of arguments in natural language can be represented in structured arguments. Finally, we discuss how distributed argumentation technology can be used to advance risk management, regulatory compliance of distributed ledgers for financial securities, and dialogue techniques.

Integrated communication and learning towards autonomous mobile radio networks

The integration of distributed and ubiquitous intelligence has emerged over the last years as the mainspring of transformative advancements in mobile radio networks. As we approach the era of “mobile for intelligence”, next-generation wireless networks are poised to undergo significant and profound changes. Notably, the overarching challenge that lies ahead is the development and implementation of integrated communication and learning mechanisms that will enable the realization of autonomous mobile radio networks. The ultimate pursuit of eliminating human-in-the-loop constitutes an ambitious challenge, necessitating a meticulous delineation of the fundamental characteristics that artificial intelligence (AI) should possess to effectively achieve this objective. This challenge represents a paradigm shift in the design, deployment, and operation of wireless networks, where conventional, static configurations give way to dynamic, adaptive, and AI-native systems capable of self-optimization, self-sustainment, and learning. This thesis aims to provide a comprehensive exploration of the fundamental principles and practical approaches required to create autonomous mobile radio networks that seamlessly integrate communication and learning components. The first chapter of this thesis introduces the notion of Predictive Quality of Service (PQoS) and adaptive optimization and expands upon the challenge to achieve adaptable, reliable, and robust network performance in dynamic and ever-changing environments. The subsequent chapter delves into the revolutionary role of generative AI in shaping next-generation autonomous networks. This chapter emphasizes achieving trustworthy uncertainty-aware generation processes with the use of approximate Bayesian methods and aims to show how generative AI can improve generalization while reducing data communication costs. Finally, the thesis embarks on the topic of distributed learning over wireless networks. Distributed learning and its declinations, including multi-agent reinforcement learning systems and federated learning, have the potential to meet the scalability demands of modern data-driven applications, enabling efficient and collaborative model training across dynamic scenarios while ensuring data privacy and reducing communication overhead.

Extending the 2P-Kt ecosystem: CLP and Labelled LP

The ability to create hybrid systems that blend different paradigms has now become a requirement for complex AI systems usually made of more than a component. In this way, it is possible to exploit the advantages of each paradigm and exploit the potential of different approaches such as symbolic and non-symbolic approaches. In particular, symbolic approaches are often exploited for their efficiency, effectiveness and ability to manage large amounts of data, while symbolic approaches are exploited to ensure aspects related to explainability, fairness, and trustworthiness in general. The thesis lies in this context, in particular in the design and development of symbolic technologies that can be easily integrated and interoperable with other AI technologies. 2P-Kt is a symbolic ecosystem developed for this purpose, it provides a logic-programming (LP) engine which can be easily extended and customized to deal with specific needs. The aim of this thesis is to extend 2P-Kt to support constraint logic programming (CLP) as one of the main paradigms for solving highly combinatorial problems given a declarative problem description and a general constraint-propagation engine. A real case study concerning school timetabling is described to show a practical usage of the CLP(FD) library implemented. Since CLP represents only a particular scenario for extending LP to domain-specific scenarios, in this thesis we present also a more general framework: Labelled Prolog, extending LP with labelled terms and in particular labelled variables. The designed framework shows how it is possible to frame all variations and extensions of LP under a single language reducing the huge amount of existing languages and libraries and focusing more on how to manage different domain needs using labels which can be associated with every kind of term. Mapping of CLP into Labeled Prolog is also discussed as well as the benefits of the provided approach.

A Multi-Center Phase II Study (SAKK 36/06) of Single Agent Everolimus (RAD001) In Patients with Relapsed or Refractory Mantle Cell Lymphoma

Introduction: Mantle cell lymphoma (MCL) accounts for 6% of all B-cell lymphomas and remains incurable for most patients. Those who relapse after first line therapy or hematopoietic stem cell transplantation have a dismal prognosis with short response duration after salvage therapy. On a molecular level, MCL is characterised by the translocation t[11;14] leading to Cyclin D1 overexpression. Cyclin D1 is downstream of the mammalian target of rapamycin (mTOR) kinase and can be effectively blocked by mTOR inhibitors such as temsirolimus. We set out to define the single agent activity of the orally available mTOR inhibitor everolimus (RAD001) in a prospective, multi-centre trial in patients with relapsed or refractory MCL (NCT00516412). The study was performed in collaboration with the EU-MCL network. Methods: Eligible patients with histologically/cytologically confirmed relapsed (not more than 3 prior lines of systemic treatment) or refractory MCL received everolimus 10 mg orally daily on day 1 - 28 of each cycle (4 weeks) for 6 cycles or until disease progression. The primary endpoint was the best objective response with adverse reactions, time to progression (TTP), time to treatment failure, response duration and molecular response as secondary endpoints. A response rate of 10% was considered uninteresting and, conversely, promising if 30%. The required sample size was 35 pts using the Simon's optimal two-stage design with 90% power and 5% significance. Results: A total of 36 patients with 35 evaluable patients from 19 centers were enrolled between August 2007 and January 2010. The median age was 69.4 years (range 40.1 to 84.9 years), with 22 males and 13 females. Thirty patients presented with relapsed and 5 with refractory MCL with a median of two prior therapies. Treatment was generally well tolerated with anemia (11%), thrombocytopenia (11%), neutropenia (8%), diarrhea (3%) and fatigue (3%) being the most frequent complications of CTC grade III or higher. Eighteen patients received 6 or more cycles of everolimus treatment. The objective response rate was 20% (95% CI: 8-37%) with 2 CR, 5 PR, 17 SD, and 11 PD. At a median follow-up of 6 months, TTP was 5.45 months (95% CI: 2.8-8.2 months) for the entire population and 10.6 months for the 18 patients receiving 6 or more cycles of treatment. Conclusion: This study demonstrates that single agent everolimus 10 mg once daily orally is well tolerated. The null hypothesis of inactivity could be rejected indicating a moderate anti-lymphoma activity in relapsed/refractory MCL. Further studies of either everolimus in combination with chemotherapy or as single agent for maintenance treatment are warranted in MCL.

A Multi-Center Phase II Study (SAKK 36/06) of Single Agent Everolimus (RAD001) In Patients with Relapsed or Refractory Mantle Cell Lymphoma

Introduction: Mantle cell lymphoma (MCL) accounts for 6% of all B-cell lymphomas and remains incurable for most patients. Those who relapse after first line therapy or hematopoietic stem cell transplantation have a dismal prognosis with short response duration after salvage therapy. On a molecular level, MCL is characterised by the translocation t[11;14] leading to Cyclin D1 overexpression. Cyclin D1 is downstream of the mammalian target of rapamycin (mTOR) kinase and can be effectively blocked by mTOR inhibitors such as temsirolimus. We set out to define the single agent activity of the orally available mTOR inhibitor everolimus (RAD001) in a prospective, multi-centre trial in patients with relapsed or refractory MCL (NCT00516412). The study was performed in collaboration with the EU-MCL network. Methods: Eligible patients with histologically/cytologically confirmed relapsed (not more than 3 prior lines of systemic treatment) or refractory MCL received everolimus 10 mg orally daily on day 1 - 28 of each cycle (4 weeks) for 6 cycles or until disease progression. The primary endpoint was the best objective response with adverse reactions, time to progression (TTP), time to treatment failure, response duration and molecular response as secondary endpoints. A response rate of ≤ 10% was considered uninteresting and, conversely, promising if ≥ 30%. The required sample size was 35 pts using the Simon's optimal two-stage design with 90% power and 5% significance. Results: A total of 36 patients with 35 evaluable patients from 19 centers were enrolled between August 2007 and January 2010. The median age was 69.4 years (range 40.1 to 84.9 years), with 22 males and 13 females. Thirty patients presented with relapsed and 5 with refractory MCL with a median of two prior therapies. Treatment was generally well tolerated with anemia (11%), thrombocytopenia (11%), neutropenia (8%), diarrhea (3%) and fatigue (3%) being the most frequent complications of CTC grade III or higher. Eighteen patients received 6 or more cycles of everolimus treatment. The objective response rate was 20% (95% CI: 8-37%) with 2 CR, 5 PR, 17 SD, and 11 PD. At a median follow-up of 6 months, TTP was 5.45 months (95% CI: 2.8-8.2 months) for the entire population and 10.6 months for the 18 patients receiving 6 or more cycles of treatment. Conclusion: This study demonstrates that single agent everolimus 10 mg once daily orally is well tolerated. The null hypothesis of inactivity could be rejected indicating a moderate anti-lymphoma activity in relapsed/refractory MCL. Further studies of either everolimus in combination with chemotherapy or as single agent for maintenance treatment are warranted in MCL.

Heterogeneous Multi-core Architectures for High Performance Computing

This thesis deals with heterogeneous architectures in standard workstations. Heterogeneous architectures represent an appealing alternative to traditional supercomputers because they are based on commodity components fabricated in large quantities. Hence their price-performance ratio is unparalleled in the world of high performance computing (HPC). In particular, different aspects related to the performance and consumption of heterogeneous architectures have been explored. The thesis initially focuses on an efficient implementation of a parallel application, where the execution time is dominated by an high number of floating point instructions. Then the thesis touches the central problem of efficient management of power peaks in heterogeneous computing systems. Finally it discusses a memory-bounded problem, where the execution time is dominated by the memory latency. Specifically, the following main contributions have been carried out: A novel framework for the design and analysis of solar field for Central Receiver Systems (CRS) has been developed. The implementation based on desktop workstation equipped with multiple Graphics Processing Units (GPUs) is motivated by the need to have an accurate and fast simulation environment for studying mirror imperfection and non-planar geometries. Secondly, a power-aware scheduling algorithm on heterogeneous CPU-GPU architectures, based on an efficient distribution of the computing workload to the resources, has been realized. The scheduler manages the resources of several computing nodes with a view to reducing the peak power. The two main contributions of this work follow: the approach reduces the supply cost due to high peak power whilst having negligible impact on the parallelism of computational nodes. from another point of view the developed model allows designer to increase the number of cores without increasing the capacity of the power supply unit. Finally, an implementation for efficient graph exploration on reconfigurable architectures is presented. The purpose is to accelerate graph exploration, reducing the number of random memory accesses.