DR-NEGOTIATE - A System for Automated Agent Negotiation with Defeasible Logic-Based Strategies

This paper reports on a system for automated agent negotiation. It uses the JADE agent framework, and its major distinctive feature is the use of declarative negotiation strategies. The negotiation strategies are expressed in a declarative rules language, defeasible logic and are applied using the implemented defeasible reasoning system DR-DEVICE. The choice of defeasible logic is justified. The overall system architecture is described, and a particular negotiation case is presented in detail

Improving interoperability among learning objects using FIPA agent communication framework

The reusability of learning material is based on three main features: modularity, discoverability and interoperability. Several researchers on Intelligent Learning Environments have proposed the use of architectures based on agent societies. Learning systems based on Multi-Agent architectures support the development of more interactive and adaptable systems and the Learning Objects approach gives reusability. We proposed an approach where learning objects are built based on agent architectures. This paper discusses how the Intelligent Learning Objects approach can be used to improve the interoperability between learning objects and pedagogical agents.Applications in Artificial Intelligence - AgentsRed de Universidades con Carreras en Informática (RedUNCI

Chapter Leveraging Internet-of-Things to Support Circular Economy Paradigm in Manufacturing Industry

Circular economy represents a fundamental alternative to the currently predominating linear economy model, while Industry 4.0 is a technological enabler to bring process innovation in the industrial domain. New economic models are needed in order to reduce material inputs and waste generation leveraging on ecodesign, recycling and reusing of products, new business models, and new technologies. Internet-of-Things and artificial intelligence can support the circular economy paradigm, through the development of a marketplace for connecting buyers and sellers of manufacturing services, raw materials and products toward building global supply chains. The core component of this marketplace is a novel, agent-based, brokering module that will apply both syntactic and semantic matching in terms of manufacturing capabilities, in order to find the best possible supplier to fulfill a request for a service, raw materials or products involved in the supply chain

Leveraging Internet-of-Things to Support Circular Economy Paradigm in Manufacturing Industry

Circular economy represents a fundamental alternative to the currently predominating linear economy model, while Industry 4.0 is a technological enabler to bring process innovation in the industrial domain. New economic models are needed in order to reduce material inputs and waste generation leveraging on ecodesign, recycling and reusing of products, new business models, and new technologies. Internet-of-Things and artificial intelligence can support the circular economy paradigm, through the development of a marketplace for connecting buyers and sellers of manufacturing services, raw materials and products toward building global supply chains. The core component of this marketplace is a novel, agent-based, brokering module that will apply both syntactic and semantic matching in terms of manufacturing capabilities, in order to find the best possible supplier to fulfill a request for a service, raw materials or products involved in the supply chain

A new model for solution of complex distributed constrained problems

In this paper we describe an original computational model for solving different types of Distributed Constraint Satisfaction Problems (DCSP). The proposed model is called Controller-Agents for Constraints Solving (CACS). This model is intended to be used which is an emerged field from the integration between two paradigms of different nature: Multi-Agent Systems (MAS) and the Constraint Satisfaction Problem paradigm (CSP) where all constraints are treated in central manner as a black-box. This model allows grouping constraints to form a subset that will be treated together as a local problem inside the controller. Using this model allows also handling non-binary constraints easily and directly so that no translating of constraints into binary ones is needed. This paper presents the implementation outlines of a prototype of DCSP solver, its usage methodology and overview of the CACS application for timetabling problems