MACIV - A DAI BASED RESOURCE-MANAGEMENT SYSTEM

Managing resources in the framework of the civil construction sector i s usually an extremely complex task. There are many factors contributi ng to this complexity: the variety and great number of existing resour ces, both human and material; the diversity of tasks that each working unit is able to execute; the performance of each working unit; the in volved costs; and the spatial distribution of all resources over the d ifferent places, leading to the need for displacement from one site to another. All these important factors imply a high number of variables , resulting in a somewhat difficult optimization process. On the other hand, these factors are highly dynamic as a result of unpredictable s ituations responsible for the modification of the initial conditions, e.g., weather conditions, uncertainties attached to task duration, acq uisition of new resources, technical problems related with those resou rces, and accidents. Such dynamics make it mandatory for the systems t o have the capability to continuously adapt themselves to the evolving real conditions, overcoming usual limitations of classical inflexible solutions. To handle this problem, we set up MACIV a project whose go al is to design and implement a computer system, mainly based on distr ibuted artificial intelligence techniques, enabling a decentralized ma nagement of the different available resources in civil construction co mpanies. This problem was inspired by an existing large company whose experts are collaborating with us, both in the problem definition and in the system design phases. In this article, the overall multiagent s ystem architecture is presented, and the employed techniques are expla ined, with special emphasis on our own contributions to the specific n egotiation and agents' coalition formation protocols. In order to supp ort the particulars of the application, original intercoalition and in tracoalition negotiation algorithms and strategies were developed and are explained here. Finally an application example is described in ord er to illustrate how our proposal enables the system to reach a goad s olution for a concrete scenario.