Negotiation with reaction functions for solving complex task allocation problems

Abstract-We study task-allocation problems where cooperative robots need to perform tasks simultaneously. We develop a distributed negotiation procedure that allows robots to find all task exchanges that reduce the team cost of a given task allocation, without robots having to know how other robots compute their robot costs. Finally, we demonstrate empirically that our negotiation procedure can substantially reduce the team costs of task allocations resulting from existing taskallocation procedures, including sequential single-item auctions

Negotiation with reaction functions for solving complex task allocation problems

Abstract-We study task-allocation problems where cooperative robots need to perform tasks simultaneously. We develop a distributed negotiation procedure that allows robots to find all task exchanges that reduce the team cost of a given task allocation, without robots having to know how other robots compute their robot costs. Finally, we demonstrate empirically that our negotiation procedure can substantially reduce the team costs of task allocations resulting from existing taskallocation procedures, including sequential single-item auctions

Production/maintenance cooperative scheduling using multi-agents and fuzzy logic

Within companies, production is directly concerned with the manufacturing schedule, but other services like sales, maintenance, purchasing or workforce management should also have an influence on this schedule. These services often have together a hierarchical relationship, i.e. the leading function (most of the time sales or production) generates constraints defining the framework within which the other functions have to satisfy their own objectives. We show how the multi-agent paradigm, often used in scheduling for its ability to distribute decision-making, can also provide a framework for making several functions cooperate in the schedule performance. Production and maintenance have been chosen as an example: having common resources (the machines), their activities are actually often conflicting. We show how to use a fuzzy logic in order to model the temporal degrees of freedom of the two functions, and show that this approach may allow one to obtain a schedule that provides a better compromise between the satisfaction of the respective objectives of the two functions

Aha? Is Creativity Possible in Legal Problem Solving and Teachable in Legal Education?

This article continues and expands on my earlier project of seeking to describe how legal negotiation should be understood conceptually and undertaken behaviorally to produce better solutions to legal problems. As structured problem solving requires interests, needs and objectives identification, so too must creative solution seeking have its structure and elements in order to be effectively taught. Because research and teaching about creativity and how we think has expanded greatly since modern legal negotiation theory has been developed, it is now especially appropriate to examine how we might harness this new learning to how we might examine and teach legal creativity in the context of legal negotiation and problem solving. This article explores both the cognitive and behavioral dimensions of legal creativity and offers suggestions for how it can be taught more effectively in legal education, both within the more narrow curricula of negotiation courses and more generally throughout legal education

Cooperative transportation scheduling : an application domain for DAI

A multiagent approach to designing the transportation domain is presented. The MARS system is described which models cooperative order scheduling within a society of shipping companies. We argue why Distributed Artificial Intelligence (DAI) offers suitable tools to deal with the hard problems in this domain. We present three important instances for DAI techniques that proved useful in the transportation application: cooperation among the agents, task decomposition and task allocation, and decentralised planning. An extension of the contract net protocol for task decomposition and task allocation is presented; we show that it can be used to obtain good initial solutions for complex resource allocation problems. By introducing global information based upon auction protocols, this initial solution can be improved significantly. We demonstrate that the auction mechanism used for schedule optimisation can also be used for implementing dynamic replanning. Experimental results are provided evaluating the performance of different scheduling strategies

EFFICIENT TEAM BUILDING FOR ON-TIME PROJECTS

When we think to software development projects we consider that a strong set of requirements is defined and team members always follow initial planning. Well, this was a specific orientation in traditional software developments methods and methodologies. In a current competitive business environment this attitude leads to fail in software development projects. This paper aims to highlight the importance of agile approach focused on meetings and team building and to give examples based on our experience in software development in industrial field for financial and energy sectors. This paper is the result of collaboration between university (business informatics, psychology, and finance) and business environment (internal software development projects).agile software development, team/group building, CMMI, project management

A multi-agent system with application in project scheduling

The new economic and social dynamics increase project complexity and makes scheduling problems more difficult, therefore scheduling requires more versatile solutions as Multi Agent Systems (MAS). In this paper the authors analyze the implementation of a Multi-Agent System (MAS) considering two scheduling problems: TCPSP (Time-Constrained Project Scheduling), and RCPSP (Resource-Constrained Project Scheduling). The authors propose an improved BDI (Beliefs, Desires, and Intentions) model and present the first the MAS implementation results in JADE platform.multi-agent architecture, scheduling, project management, BDI architecture, JADE.

Knowledge-Based Support for Management of Concurrent, Multidisciplinary Design

Artificial intelligence (AI) applications to design have tended to focus on modeling and automating aspects of single discipline design tasks. Relatively little attention has thus far been devoted to representing the kinds of design \u27metaknowledge\u27 needed to manage the important interface issues that arise in concurrent design, that is, multidisciplinary design decision-making. This paper provides a view of the process and management of concurrent design and evaluates the potential of two AI approaches—blackboard architectures and co-operative distributed problem-solving (CDPS)—to model and support the concurrent design of complex artifacts. A discussion of the process of multidisciplinary design highlights elements of both sequential and concurrent design decision-making. We identify several kinds of design metaknowledge used by expert managers to: partition the design task for efficient execution by specialists; set appropriate levels of design conservatism for key subsystem specifications; evaluate, limit and selectively communicate design changes across discipline boundaries; and control the sequence and timing of the key (highly constrained and constraining) design decisions for a given type of artifact. We explore the extent to which blackboard and CDPS architectures can provide valid models of and potential decision support for concurrent design by (1) representing design management metaknowledge, and (2) using it to enhance both horizontal (interdisciplinary) and vertical (project life cycle) integration among product design, manufacturing and operations specialists