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Electronic commerce and finance are progressively supporting and including decentralized, shared and public ledgers such as the blockchain. This is reshaping traditional commercial activities by advancing them towards Decentralized Finance(DeFi) and Commerce 3.0, thereby supporting the latter’s potential to outpace the hurdles of central authority controllers and lawgivers. The quantity and entropy of the information that must be sought and managed to become active participants in such a relentlessly evolving scenario are increasing at a steady pace. For example, that information comprises asset or service description, general rules of the game, and specific technologies involved for decentralization. Moreover, the relevant information ought to be shared among innumerable and heterogeneous stakeholders, such as producers, buyers, digital identity providers, valuation services, and shipment services, to just name a few. A clear semantic representation of such a complex and multifaceted blockchain-based e-Commerce ecosystem would contribute dramatically to make it more usable, namely more automatically accessible to virtually anyone wanting to play the role of a stakeholder, thereby reducing programmers’ effort. However, we feel that reaching that goal still requires substantial effort in the tailoring of Semantic Web technologies, hence this article sets out on such a route and advances a stack of OWL 2 ontologies for the semantic description of decentralized e-commerce. The stack includes a number of relevant features, ranging from the applicable stakeholders through the supply chain of the offerings for an asset, up to the Ethereumblockchain, its tokens and smart contracts. Ontologies are defined by taking a behaviouristic approach to represent the various participants as agents in terms of their actions, inspired by the Theory of Agentsand the related mentalistic notions. The stack is validated through appropriate metrics and SPARQL queries implementing suitable competency questions, then demonstrated through the representation of a real world use case, namely, the iExec marketplace.

Semantic representation is a key enabler for several application domains, and the multi-agent systems realm makes no exception. Among the methods for semantically representing agents, one has been essentially achieved by taking a behaviouristic vision, through which one can describe how they operate and engage with their peers. The approach essentially aims at defining the operational capabilities of agents through the mental states related with the achievement of tasks. The OASIS ontology — An Ontology for Agent, Systems, and Integration of Services, presented in 2019 — pursues the behaviouristic approach to deliver a semantic representation system and a communication protocol for agents and their commitments. This paper reports on the main modelling choices concerning the representation of agents in OASIS 2, the latest major upgrade of OASIS, and the achievement reached by the ontology since it was first introduced, in particular in the context of ontologies for blockchains.

The interoperability of devices from distinct brands on the Internet of Things (IoT) domain is still an open issue. The main reason is that pioneer companies always deliberately neglected to deploy devices able to interoperate with competitors products. The key factors that may invert such a trend derive, on one hand, from the abstraction of communication protocols that facilitates the migration from vertical to horizontal paradigms and, on the other hand, from the introduction of common and shared ontologies encoding devices specifications. The Semantic Web, with all its layers, can be considered the main framework for delivering ontologies, and by virtue of its features, it is surely the ideal means for providing shared knowledge. In this paper we present a framework that instantiates cognitiveagents operating in IoT context, endowed with meta-reasoning in the Semantic Web. The framework, called SW-Caspar, is also provided with a module that performs semi-automatic ontology learning from sentences expressed in natural language; such a learning process generates a conceptual space reflecting the domain of discourse with an instance of a novel foundational ontology called Linguistic Oriented Davidsonian Ontology(LODO), whose main feature is to increase the deepness of reasoning without compromising linguistic-related features. LODO is inspired by the First-Order Logic Davidsonian notation and is serialized in OWL 2. Well-known examples derived from the theory of logical reasoning and a case-study applied to automation on health scenarios are also provided.

We solve the satisfiability problem for a three-sorted fragment of set theory (denoted 3LQST 0 R ), which admits a restricted form of quantification over individual and set variables and the finite enumeration operator {-,-,...,-} over individual variables, by showing that it enjoys a small model property, i.e., any satisfiable formula ψ of 3 LQST 0 R has a finite model whose size depends solely on the length of ψ itself. Several set-theoretic constructs are expressible by 3 LQST 0 R -formulae, such as some variants of the power set operator and the unordered Cartesian product. In particular, concerning the latter construct, we show that when finite enumerations are allowed, the resulting formula is exponentially shorter than in their absence. [ABSTRACT FROM AUTHOR]

We describe a relational framework that uniformly supports formalization and automated reasoning in varied propositional modal logics. The proof system we propose is a relational variant of the classical Rasiowa-Sikorski proof system. We introduce a compact graph-based representation of formulae and proofs supporting an efficient implementation of the basic inference engine, as well as of a number of refinements. Completeness and soundness results are shown and a Prolog implementation is described.