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Last name: PULINA
First name: Luca
In this paper we provide a concise survey of our work devoted to applying formal methods to check the safety of adaptive cyber-physical systems.
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Maintaining updated ontology-based digital libraries faces two main issues. First, documents are often unstructured and in heterogeneous data formats, making it even more difficult to extract information and search in. Second, manual ontology population is time consuming and therefore automatic methods to support this process are needed. In...
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Reinforcement Learning is a well-known AI paradigm whereby control policies of autonomous agents can be synthesized in an incremental fashion with little or no knowledge about the properties of the environment. We are concerned with safety of agents whose policies are learned by reinforcement, i.e., we wish to bound the risk that, once learning...
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Ensuring safe behaviors, i.e., minimizing the probability that a control strategy yields undesirable effects, becomes crucial when robots interact with humans in semi-structured environments through adaptive control strategies. In previous papers, we contributed to propose an approach that (i) computes control policies through reinforcement...
In the context of Requirements Engineering, checking the consistency of functional requirements is an important and still mostly open problem. In case of requirements written in natural language, the corresponding manual review is time consuming and error prone. On the other hand, automated consistency checking most often requires overburdening...
Property Specification Patterns (PSPs) have been proposed to solve recurring specification needs, to ease the formalization of requirements, and enable automated verification thereof. In this paper, we extend PSPs by considering Boolean as well as atomic numerical assertions. This extension enables us to reason about functional requirements...
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