An Approach to Agent-Based Service Composition and Its Application to Mobile

This paper describes an architecture model for multiagent systems that was developed in the European project LEAP (Lightweight Extensible Agent Platform). Its main feature is a set of generic services that are implemented independently of the agents and can be installed into the agents by the application developer in a flexible way. Moreover, two applications using this architecture model are described that were also developed within the LEAP project. The application domain is the support of mobile, virtual teams for the German automobile club ADAC and for British Telecommunications

MASDScheGATS - Scheduling System for Dynamic Manufacturing Environmemts

This chapter addresses the resolution of scheduling in manufacturing systems subject to perturbations. The planning of Manufacturing Systems involves frequently the resolution of a huge amount and variety of combinatorial optimisation problems with an important impact on the performance of manufacturing organisations. Examples of those problems are the sequencing and scheduling problems in manufacturing management, routing and transportation, layout design and timetabling problems

Cooperative Multi-Agent Systems from the Reinforcement Learning Perspective -- Challenges, Algorithms, and an Application

Reinforcement Learning has established as a framework that allows an autonomous agent for automatically acquiring -- in a trial and error-based manner -- a behavior policy based on a specification of the desired behavior of the system. In a multi-agent system, however, the decentralization of the control and observation of the system among independent agents has a significant impact on learning and it complexity. In this survey talk, we briefly review the foundations of single-agent reinforcement learning, point to the merits and challenges when applied in a multi-agent setting, and illustrate its potential in the context of an application from the field of manufacturing control and scheduling

Design choices for agent-based control of AGVs in the dough making process

In this paper we consider a multi-agent system (MAS) for the logistics control of Automatic Guided Vehicles (AGVs) that are used in the dough making process at an industrial bakery. Here, logistics control refers to constructing robust schedules for all transportation jobs. The paper discusses how alternative MAS designs can be developed and compared using cost, frequency of messages between agents, and computation time for evaluating control rules as performance indicators. Qualitative design guidelines turn out to be insufficient to select the best agent architecture. Therefore, we also use simulation to support decision making, where we use real-life data from the bakery to evaluate several alternative designs. We find that architectures in which line agents initiate allocation of transportation jobs, and AGV agents schedule multiple jobs in advance, perform best. We conclude by discussing the benefits of our MAS systems design approach for real-life applications

Distributed Consensus to Enable Merging and Spacing of UAS in an Urban Environment

This paper presents a novel approach to enable multiple Unmanned Aerial Systems approaching a common intersection to independently schedule their arrival time while maintaining a safe separation. Aircraft merging at a common intersection are grouped into a network and each aircraft broadcasts its arrival time interval to the network. A distributed consensus algorithm elects a leader among the aircraft approaching the intersection and helps synchronize the information received by each aircraft. The consensus algorithm ensures that each aircraft computes a schedule with the same input information. The elected leader also dictates when a schedule must be computed, which may be triggered when a new aircraft joins the network. Preliminary results illustrating the collaborative behavior of the vehicles are presented

From supply chains to demand networks. Agents in retailing: the electrical bazaar

A paradigm shift is taking place in logistics. The focus is changing from operational effectiveness to adaptation. Supply Chains will develop into networks that will adapt to consumer demand in almost real time. Time to market, capacity of adaptation and enrichment of customer experience seem to be the key elements of this new paradigm. In this environment emerging technologies like RFID (Radio Frequency ID), Intelligent Products and the Internet, are triggering a reconsideration of methods, procedures and goals. We present a Multiagent System framework specialized in retail that addresses these changes with the use of rational agents and takes advantages of the new market opportunities. Like in an old bazaar, agents able to learn, cooperate, take advantage of gossip and distinguish between collaborators and competitors, have the ability to adapt, learn and react to a changing environment better than any other structure. Keywords: Supply Chains, Distributed Artificial Intelligence, Multiagent System.Postprint (published version

Realising Team-Working in the Field: An Agent-based Approach

Multi-agent systems technology is applied to enable co-operation between mobile workers in the field, minimising user intervention and increasing reachability. A component-based approach is taken to simplify the management of deployed co-operation services. A Personal Assistant running on a mobile device is introduced to show how an intelligent and autonomous agent can increase the utility of users during workforce co-operation processes. Finally, a real world trial of the technology by network installation and maintenance engineers in the UK is described. Some technical issues revealed during the trial are discussed, as is the impact of the technology on the business process

Assessing the potential of decentralised scheduling: An experimental study for the job shop case

-Part of special issue: 10th IFAC Conference on Manufacturing Modelling, Management and Control MIM 2022: Nantes, France, 22-24 June 2022. -Copyright © 2022 The Authors. This is an open access article under the CC BY-NC-ND license.In this paper we investigate how decentralised scheduling approaches can be used to improve manufacturing scheduling. In view of the potential shown by some of these novel decentralised approaches, we conduct a series of experiments on a set of job shop instances subject to different degrees of variability in their processing times, and compare the performance of different scoring methods under the Contract Net Protocol proposed by Guizzi et al. (2019) with the objective of minimizing the expected makespan. We also compare the performance of the optimal (centralised and deterministic) solution in the stochastic setting, as well as a hybrid centralised-decentralised approach. Despite some limitations in the experiments, the results show the excellent performance of the decentralised approach if its operating parameters are optimized, and that the hybrid approach serves to overcome some of the problems of both centralised and decentralised approaches