Semantics for hierarchical task-network planning
Semantics for hierarchical task-network planning
The RAPPID Project: Symbiosis between Industrial Requirements and MAS Research
Autonomous Agents and Multi-Agent Systems
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Autonomous Agents and Multi-Agent Systems
OIL Ontologies for Collaborative Task Performance in Coalitions of Self-Interested Actors
Revised Papers from the HUMACS, DASWIS, ECOMO, and DAMA on ER 2001 Workshops
The Knowledge Engineering Review
Applying ADELFE Methodology to a Mechanism Design Problem
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 3
Multi-agent system development kit: MAS software tool implementing Gaia methodology
Intelligent information processing II
Agent-Based framework for simulation and support of dynamic engineering design processes in PSI
CEEMAS'05 Proceedings of the 4th international Central and Eastern European conference on Multi-Agent Systems and Applications
Managing Concurrent Engineering Design Processes and Associated Knowledge
Proceedings of the 2006 conference on Leading the Web in Concurrent Engineering: Next Generation Concurrent Engineering
An agent-oriented model of a dynamic engineering design process
AOIS'05 Proceedings of the 7th international conference on Agent-Oriented Information Systems III
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One way to make engineering design effective and efficient is to make its processes flexible – i.e. self-adjusting, self-configuring, and self-optimizing at run time. This paper presents the descriptive part of the Dynamic Engineering Design Process (DEDP) modeling framework developed in the PSI project. The project aims to build a software tool to assist managers to analyze and enhance the productivity of the DEDPs through process simulations. The framework incorporates the models of teams and actors, tasks and activities as well as design artifacts as the major interrelated parts. DEDPs are modeled as weakly defined flows of tasks and atomic activities which may only “become apparent” at run time because of several presented dynamic factors. The processes are self-formed through the mechanisms of collaboration in the dynamic team of actors. These mechanisms are based on several types of contracting negotiations. DEDP productivity is assessed by the Units of Welfare collected by the multi-agent system which models the design team. The models of the framework are formalized in the family of DEDP ontologies.