Artificial intelligence: a new synthesis
Artificial intelligence: a new synthesis
Introduction to Multiagent Systems
Introduction to Multiagent Systems
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
Multiagent planning for agents with internal execution resource constraints
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Structure and complexity in planning with unary operators
Journal of Artificial Intelligence Research
Fast planning through planning graph analysis
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
MECIMPLAN: an agent-based methodology for planning
International Journal of Intelligent Information and Database Systems
Defining and monitoring strategically aligned software improvement goals
PROFES'10 Proceedings of the 11th international conference on Product-Focused Software Process Improvement
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Despite the wide range of problems in which planning is used, it is possible to utilize a common methodology that allows us to reach specific planning objectives for a real problem. From a software engineering point of view, the methodology assures us the quality of the process and the product. In this paper we introduce a methodology that permits us to construct models in order to solve planning problems at any project environment through the use of agents. We have built a prototype for Strategic Planning that presents us with an alternative solution to the well-known 'Prospective' technique. It is particularly relevant for planning problems that are concerned with decisions that have a long-term impact. The results obtained through the construction of prototypes illustrate the adequacy of our approach. This paper is organized as follows: we first give a general overview of the methodology. In Section 2, we illustrate the approach by a case study in the domain of strategic planning. Section 3 presents an agent-based prototype that implements the case study. We conclude the paper by stating the lessons learnt from this enterprise.