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This paper presents an efficient cyberphysical platform for the smart management of smart territories. It is efficient because it facilitates the implementation of data acquisition and data management methods, as well as data representation and dashboard configuration. The platform allows for the use of any type of data source, ranging from the measurements of a multi-functional IoT sensing devices to relational and non-relational databases. It is also smart because it incorporates a complete artificial intelligence suit for data analysis; it includes techniques for data classification, clustering, forecasting, optimization, visualization, etc. It is also compatible with the edge computing concept, allowing for the distribution of intelligence and the use of intelligent sensors. The concept of smart cities is evolving and adapting to new applications; the trend to create intelligent neighbourhoods, districts or territories is becoming increasingly popular, as opposed to the previous approach of managing an entire megacity. In this paper, the platform is presented, and its architecture and functionalities are described. Moreover, its operation has been validated in a case study where the bike renting service of Paris—Vélib’ Métropole has been managed. This platform could enable smart territories to develop adapted knowledge management systems, adapt them to new requirements and to use multiple types of data, and execute efficient computational and artificial intelligence algorithms. The platform optimizes the decisions taken by human experts through explainable artificial intelligence models that obtain data from IoT sensors, databases, the Internet, etc. The global intelligence of the platform could potentially coordinate its decision-making processes with intelligent nodes installed in the edge, which would use the most advanced data processing techniques., POCTEP, DCSC/LAPASSION, CITIES, Depto. de Ingeniería de Software e Inteligencia Artificial (ISIA), Fac. de Informática, TRUE, pub

There have been many attempts to integrate automated planning and rational agents. Most of the research focuses on adding support directly within agent programming languages, such as those based on the Belief-Desire-Intention model, rather than using off-the-shelf planners. This approach is often believed to improve the computation time, which is a common requirement in real world applications. This paper shows that even in complex scenarios, such as in the Multi-Agent Programming Contest with 50 agents and a 4 s deadline for the agents to send actions to the server, it is possible to efficiently integrate agent languages with off-the-shelf automated planners. Based on the experience with this case study, the paper discusses advantages and disadvantages of decoupling the agents from the planners.

There have been many attempts to integrate automated planning and rational agents. Most of the research focuses on adding support directly within agent programming languages, such as those based on the Belief-Desire-Intention model, rather than using off-the-shelf planners. This approach is often believed to improve the computation time, which is a common requirement in real world applications. This paper shows that even in complex scenarios, such as in the Multi-Agent Programming Contest with 50 agents and a 4 s deadline for the agents to send actions to the server, it is possible to efficiently integrate agent languages with off-the-shelf automated planners. Based on the experience with this case study, the paper discusses advantages and disadvantages of decoupling the agents from the planners.

There is a wide range of military and civil applications where Wireless Sensor Networks (WSNs) and Multi- Agent Systems (MASs) can be used for providing contextawareness for troops and special corps. On the one hand, WSNs comprise an ideal technology to develop Real-Time Locating Systems (RTLSs) aimed at indoor environments, where existing global navigation satellite systems do not work properly. On the other hand, agent-based architectures allow building autonomous and robust systems that are capable of working on highly dynamic scenarios. This paper presents two piracy scenarios where the n-Core platform can be applied. n-Core is a hardware and software platform intended for developing and deploying easily and quickly a wide variety of WSNs applications based on the ZigBee standard. In the first scenario a RTLS is deployed to support boarding and rescue operations. In the second scenario a multi-agent system is proposed to detect the unloading of illegal traffic of merchandise at ports.