Valerio Senni

AI
3papers
27citations
Novelty25%
AI Score16

3 Papers

LODec 2, 2014
Proceedings First Workshop on Horn Clauses for Verification and Synthesis

Nikolaj Bjørner, Fabio Fioravanti, Andrey Rybalchenko et al.

This volume contains the proceedings of HCVS 2014, the First Workshop on Horn Clauses for Verification and Synthesis which was held on July 17, 2014 in Vienna, Austria as a satellite event of the Federated Logic Conference (FLoC) and part of the Vienna Summer of Logic (VSL 2014). HCVS 2014 was affiliated to the 26th International Conference on Computer Aided Verification (CAV 2014) and to the 30th International Conference on Logic Programming (ICLP 2014). Most Program Verification and Synthesis problems of interest can be modeled directly using Horn clauses and many recent advances in the Constraint/Logic Programming and Program Verification communities have centered around efficiently solving problems presented as Horn clauses. Since Horn clauses for verification and synthesis have been advocated by these communities in different times and from different perspectives, the HCVS workshop was organized to stimulate interaction and a fruitful exchange and integration of experiences.

AIJul 30, 2014
Backwards State-space Reduction for Planning in Dynamic Knowledge Bases

Valerio Senni, Michele Stawowy

In this paper we address the problem of planning in rich domains, where knowledge representation is a key aspect for managing the complexity and size of the planning domain. We follow the approach of Description Logic (DL) based Dynamic Knowledge Bases, where a state of the world is represented concisely by a (possibly changing) ABox and a (fixed) TBox containing the axioms, and actions that allow to change the content of the ABox. The plan goal is given in terms of satisfaction of a DL query. In this paper we start from a traditional forward planning algorithm and we propose a much more efficient variant by combining backward and forward search. In particular, we propose a Backward State-space Reduction technique that consists in two phases: first, an Abstract Planning Graph P is created by using the Abstract Backward Planning Algorithm (ABP), then the abstract planning graph P is instantiated into a corresponding planning graph P by using the Forward Plan Instantiation Algorithm (FPI). The advantage is that in the preliminary ABP phase we produce a symbolic plan that is a pattern to direct the search of the concrete plan. This can be seen as a kind of informed search where the preliminary backward phase is useful to discover properties of the state-space that can be used to direct the subsequent forward phase. We evaluate the effectiveness of our ABP+FPI algorithm in the reduction of the explored planning domain by comparing it to a standard forward planning algorithm and applying both of them to a concrete business case study.

PLJun 9, 2014
Stochastically timed predicate-based communication primitives for autonomic computing

Diego Latella, Michele Loreti, Mieke Massink et al.

Predicate-based communication allows components of a system to send messages and requests to ensembles of components that are determined at execution time through the evaluation of a predicate, in a multicast fashion. Predicate-based communication can greatly simplify the programming of autonomous and adaptive systems. We present a stochastically timed extension of the Software Component Ensemble Language (SCEL) that was introduced in previous work. Such an extension raises a number of non-trivial design and formal semantics issues with different options as possible solutions at different levels of abstraction. We discuss four of these options, of which two in more detail. We provide a formal semantics definition and an illustration of the use of the language modeling a bike sharing system, together with some preliminary analysis of the system performance.