Self-Organization through a multi-agent system for orders distribution in large companies

This article presents the development of a multi-agent system in charge of self-managing a delivery system. The article focuses on the delivery management system and not on the movement systems of the different used vehicles./nThis system consists of different types of vehicles, each with different characteristics, and there may be several instances of each type of vehicle. There will be three operating agents (Drone Operator, Car Operator and Amphibious Operator), an agent that will be responsible for creating random tasks (used only in simulations) and another one that is responsible for distributing these tasks to the operators taking into account the algorithm. This algorithm follows the bases of backtracking and its main function is to assign a task to a vehicle taking into account the distance, the consumption, the limitations of weight and distances, etc. The whole system has been developed in JADE on java. The described software performs a complete simulation with a console in which it is indicated relevant information such as the tasks that are created, the type of vehicle and the instance of that type of vehicle that resolve the delivery, among others. The purpose of this system is to minimize costs and times

SELF-ORGANIZING MOBILE ROBOTS BASED ON MULTI-AGENT COORDINATION TECHNIQUES IMPLEMENTED WITH AERIAL VISION AND COMMUNICATION GATEWAY BETWEEN WIFI AND RF

AbstractThis paper presents the development of mobile robots that have the abilities of search and retrieval of obstacles in a maze-like environment. The algorithm embedded in the robots was designed based upon principles of coordination and self-organization, i.e., a group of autonomous agents coordinate their actions in order to search and retrieve obstacles from the environment through cooperation. To do this, two types of agents were designed, organizers and operators. Organizers try to coordinate the actions of the operators, and these last, try to retrieve all obstacles in the environment. Five four-wheeled robots were built from scratch using Arduino Uno for the operators, and Arduino Nano plus NXP i.MX53 Quick Start Boards for the organizers. Also, an aerial camera (attached to the ceiling) was used to provide visual perception to the robots. The communication was made through a gateway between 8bit channel RF and WiFi, for the operators and organizers respectively.Keywords: Computer vision, mobile robots, self-organization.ROBOTS MÓVILES AUTOORGANIZADORES BASADOS EN TÉCNICAS DE COORDINACIÓN MULTIAGENTE IMPLEMENTADAS CON VISIÓN AÉREA Y PUERTA DE ENLACE DE COMUNICACIONES ENTRE WIFI Y RFResumenEste artículo presenta el desarrollo de robots móviles que poseen la capacidad de búsqueda y recuperación de obstáculos en un entorno de laberinto. El algoritmo incorporado en los robots fue diseñado con base en principios de coordinación y autoorganización, es decir, un grupo de agentes autónomos coordinan sus acciones para buscar y recuperar obstáculos del entorno a través de la cooperación. Para ello, se diseñaron dos tipos de agentes, organizadores y operadores. Los organizadores tratan de coordinar las acciones de los operadores, y estos últimos, tratan de recuperar todos los obstáculos en el medio ambiente. Cinco robots de cuatro ruedas fueron construidos desde cero utilizando Arduino Uno para los operadores, y Arduino Nano y NXP i.MX53 Quick Start Boards para los organizadores. Además, se utilizó una cámara aérea (fijada al techo) para proporcionar percepción visual a los robots. La comunicación se realizó a través de una pasarela entre el canal de 8bit RF y WiFi, para los operadores y los organizadores, respectivamente.Palabras Claves: Autoorganización, robots móviles, visión computacional

Multi-agent systems negotiation to deal with dynamic scheduling in disturbed industrial context

International audienceIt is now accepted that using multi-agent systems (MAS) improve the reactivity to treat perturbation(s) within flexible manufacturing system. Intelligent algorithms shall be used to address these perturbation(s) and all smart decision entities within their environment have to continuously negotiate until their common and final goal is achieved. This paper proposes a negotiation-based control approach to deal with variability on a manufacturing system. It has initially formulated and modeled an environment in which all contributing entities or agents operate, communicate, and interact with each other productively. Then after, simulation and applicability implementation experiments on the basis of full-sized academic experimental platform have been conducted to validate the proposed control approach. Product and resource entities negotiate considering different key performance measures in order to set best priority-based product sequencing. This has been done with expectations that the applicability of the negotiation-based decision-making will be more adaptable to deal with perturbation(s) than another alternative decision-making approach called pure reactive control approach. The result showed that negotiation among the decisional entities has brought significant improvement in reducing makespan and hence conveyed better global performance of a manufacturing system

Concepts and Methods from Artificial Intelligence in Modern Information Systems – Contributions to Data-driven Decision-making and Business Processes

Today, organizations are facing a variety of challenging, technology-driven developments, three of the most notable ones being the surge in uncertain data, the emergence of unstructured data and a complex, dynamically changing environment. These developments require organizations to transform in order to stay competitive. Artificial Intelligence with its fields decision-making under uncertainty, natural language processing and planning offers valuable concepts and methods to address the developments. The dissertation at hand utilizes and furthers these contributions in three focal points to address research gaps in existing literature and to provide concrete concepts and methods for the support of organizations in the transformation and improvement of data-driven decision-making, business processes and business process management. In particular, the focal points are the assessment of data quality, the analysis of textual data and the automated planning of process models. In regard to data quality assessment, probability-based approaches for measuring consistency and identifying duplicates as well as requirements for data quality metrics are suggested. With respect to analysis of textual data, the dissertation proposes a topic modeling procedure to gain knowledge from CVs as well as a model based on sentiment analysis to explain ratings from customer reviews. Regarding automated planning of process models, concepts and algorithms for an automated construction of parallelizations in process models, an automated adaptation of process models and an automated construction of multi-actor process models are provided

Multi-agent coordination and cooperation through classical planning

Multi-agent planning is a fundamental problem in multiagent systems that has acquired a variety of meanings in the relative literature. In this paper we focus on a setting where multiple agents with complementary capabilities cooperate in order to generate non-conflicting plans that achieve their respective goals. We study two situations. In the first, the agents are able to achieve their subgoals by themselves, but they need to find a coordinated course of action that avoids harmful interactions. In the second situation, some agents may ask the assistance of others in order to achieve their goals. We formalize the two problems and present algorithms for their solution. These algorithms are based on an underlying classical planner which is used by the agents to generate their individual plans, but also to find plans that are consistent with those of the other agents. The procedures generate optimal plans under the plan length criterion. The central role that has been given to the classical planning algorithm, can be seen as an attempt to establish a stronger link between classical and multi-agent planning.

Multi-agent Coordination and Cooperation through Classical Planning

Multi-agent planning is a fundamental problem in multiagent systems that has acquired a variety of meanings in the relative literature. In this paper we focus on a setting where multiple agents with complementary capabilities cooperate in order to generate non-conflicting plans that achieve their respective goals. We study two situations. In the first, the agents are able to achieve their subgoals by themselves, but they need to find a coordinated course of action that avoids harmful interactions. In the second situation, some agents may ask the assistance of others in order to achieve their goals. We formalize the two problems in a more general way than in previous works, and present algorithms for their solution. These algorithms are based on an underlying classical planner which is used by the agents to generate their individual plans, but also to find plans that are consistent with those of the other agents. The procedures generate optimal plans under the plan length criterion, but they can be adapted to other criteria as well. The central role that has been given to the classical planning algorithm, can be seen as an attempt to establish a stronger link between classical and multi-agent planning.