95 research outputs found
Energy Saving and Collision-Free Motion Planning for Oblivious Robots
No full textIn distributed computing, many tasks have been studied involving mobile entities - also called robots - with weak capabilities. A well-known scenario is that in which robots operate in Look-Compute-Move (LCM) cycles. During each cycle, a robot acquires a snapshot of the surrounding environment (Look phase), then executes an appropriate algorithm by using the obtained snapshot as input (Compute phase), and finally moves toward a desired destination, if any (Move phase). In this context, we consider robots that have to visit a partially ordered set of locations. A solution to the problem is the assignment to each robot of a trajectory to follow in order to visit the required locations. The resolution of the task is subject to two main constraints. Robots have to minimize the energy spent to accomplish an assigned trajectory, and they have to avoid collisions among each other. The minimization of the energy is expressed in terms of the number of turns a robot has to perform in between two different locations. This equals the number of bends the assigned trajectory contains in between such locations. In general, the problem is known to require Ω(n) bends per connection, with n being the number of locations, even if considering just two robots involved. We study the case where the locations that a single robot has to visit are represented as colored points in the Euclidean plane, and only two colors are provided. This means the partial order among the locations is just based on two colors per robot. In this case, we provide a constructive solution for two robots with five bends per connection
Shape Calculus: Timed Operational Semantics and Well-Formedness
No full textExtended version, including proofs, of Bartocci, E.; Cacciagrano, D. R.; Di Berardini, M. R.; Merelli, E. & Tesei, L. Timed Operational Semantics and Well-formedness of Shape Calculus. Scientific Annals of Computer Science, 20(1):33-52, 201
On Synchronous and Asynchronous Communication Paradigms
No full textThe pi-calculus, its asynchronous version and Boudol's mapping from the former language to the latter one are well-known mathematical objects in theoretical computer science. It is also well-known that the mapping is not fully-abstract w.r.t. most of the semantics defined over these two languages. In this paper we study and fix conditions on the existence of fully-abstract results for Boudol's mapping (and its variants). The testing theories \`a la De Nicola-Hennessy turned out to be very useful tools for such a purpose
Formal Semantics of an IoT-Specific Language
No full textA domain-specific language (DSL) is a programming language that is specialised to a particular application domain. IRON is a DSL for the IoT domain which allows not only to program solutions for the IoT by Event-Condition-Action (ECA) rules, but also prevent or report incorrect actions (from the logical point of view). The formal definition of this language is important to correctly implement interpreters avoiding contradictory, cyclical or ambiguous program configurations. To this ending, we formally define the semantics of IRON by a suitable operational rule system. The proposed operational semantics can describe the execution model of IRON programs and, at the same time, intercept several possible program anomalies (e.g., rule redundancy and circularity). Although IRON operational semantics describes a specific execution model, the proposed methodology - of encoding the IRON execution model into a "corresponding" formal operational semantics - can be also taken into account for formally defining semantics of other ECA rules based languages for IoT
ResourceHome: an RFID-based architecture and a flexible model for ambient intelligence
No full textIn this paper, we propose ResourceHome, an innovative RFID-based framework to locate objects in delimited environments and statically prevent/detect dangerous spatial/temporal configurations, i.e. configurations firing dangerous interactions of properties among objects.
Differently from most of RFID-based frameworks for spatial recognition, ResourceHome is equipped with an ontology-based knowledge model for describing two-dimensional environments
with fixed and mobile objects, as well as with a suitable First Order logic-based model for statically detecting spatial/temporal configurations of objects firing dangerous interactions
Bone Remodelling: A Complex Automata-Based Model Running in BioShape
No full textBone remodelling, as many biological phenomena, is inherently
multi-scale, i.e. it is characterised by interactions involving different scales at the same time. At this aim, we exploit the Complex Automata paradigm and the BioShape 3D spatial simulator respectively (i) for describing the bone remodelling process in terms of a 2-scale aggregation of uniform Cellular Automata coupled by a well-established composition pattern, and (ii) for executing them in a uniform and integrated way in terms of shapes equipped with perception and movement capabilities.
On the one hand, the proposed model confirms the high expressiveness degree of Complex Automata to describe multi-scale phenomena. On the other hand, the possibility of executing such a model in BioShape highlights the existence of a general mapping - from Complex Automata into the BioShape native modelling paradigm - also enforced by the fact that both approaches result to be suitable for handling different scales
in a uniform way, for including spatial information and for bypassing inter-scale homogenization problems
Fair Pi
No full textIn this paper, we define fair computations in the π-calculus [18]. We follow Costa and Stirling’s approach for CCS-like languages but exploit a more natural labeling method of process actions to filter out unfair process executions. The new labeling allows us to prove all the significant properties of the original one, such as unicity, persistence and disappearance of labels. It also turns out that the labeled pi-calculus is a conservative extension of the standard one. We contrast the existing fair testing with those that
naturally arise by imposing weak and strong fairness as defined by Costa and Stirling. This comparison provides the expressiveness of the various fair testing-based semantics and emphasizes the discriminating power of the one already proposed in the literature
Separation of synchronous and asynchronous communication via testing
No full textOne of the early results about the asynchronous π-calculus which significantly contributed to its popularity is the capability of encoding the output prefix of the (choiceless) pi-calculus in a natural and elegant way.
Encodings of this kind were proposed by Honda and Tokoro, by Nestmann and (independently) by Boudol.
We investigate whether the above encodings preserve De Nicola and Hennessy’s testing semantics. In this sense, it turns out that, under some general conditions, no encoding of output prefix is able to preserve the must testing. This negative result is due to (a) the non atomicity of the sequences of steps which are necessary in the asynchronous π-calculus to mimic synchronous communication, and (b) testing semantics’s sensitivity to divergence
Explainability and Interpretability in Concept and Data Drift: A Systematic Literature Review
No full textExplainability and interpretability have emerged as essential considerations in machine learning, particularly as models become more complex and integral to a wide range of applications. In response to increasing concerns over opaque “black-box” solutions, the literature has seen a shift toward two distinct yet often conflated paradigms: explainable AI (XAI), which refers to post hoc techniques that provide external explanations for model predictions, and interpretable AI, which emphasizes models whose internal mechanisms are understandable by design. Meanwhile, the phenomenon of concept and data drift—where models lose relevance due to evolving conditions—demands renewed attention. High-impact events, such as financial crises or natural disasters, have highlighted the need for robust interpretable or explainable models capable of adapting to changing circumstances. Against this backdrop, our systematic review aims to consolidate current research on explainability and interpretability with a focus on concept and data drift. We gather a comprehensive range of proposed models, available datasets, and other technical aspects. By synthesizing these diverse resources into a clear taxonomy, we intend to provide researchers and practitioners with actionable insights and guidance for model selection, implementation, and ongoing evaluation. Ultimately, this work aspires to serve as a practical roadmap for future studies, fostering further advancements in transparent, adaptable machine learning systems that can meet the evolving needs of real-world applications
- …
