Reasoning about action II: the qualification problem
Artificial Intelligence
Bridging the gap between planning and scheduling
The Knowledge Engineering Review
Defeasible logic programming: an argumentative approach
Theory and Practice of Logic Programming
Distributed Defeasible Contextual Reasoning in Ambient Computing
AmI '08 Proceedings of the European Conference on Ambient Intelligence
Reviving partial order planning
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Defeasible reasoning and partial order planning
FoIKS'08 Proceedings of the 5th international conference on Foundations of information and knowledge systems
Defeasible Contextual Reasoning with Arguments in Ambient Intelligence
IEEE Transactions on Knowledge and Data Engineering
Multiagent argumentation for cooperative planning in DeLP-POP
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 3
An architecture for defeasible-reasoning-based cooperative distributed planning
OTM'11 Proceedings of the 2011th Confederated international conference on On the move to meaningful internet systems - Volume Part I
What planner for ambient intelligence applications?
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Temporal defeasible argumentation in multi-agent planning
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Cooperative dialogues for defeasible argumentation-based planning
ArgMAS'11 Proceedings of the 8th international conference on Argumentation in Multi-Agent Systems
| Hi-index | 0.00 |
This contribution presents a practical extension of a theoretical model for multi-agent planning based upon DeLP, an argumentation-based defeasible logic. Our framework, named DeLP-MAPOP, is implemented on a platform for open multi-agent systems and has been experimentally tested, among others, in applications of ambient intelligence in the field of health-care. DeLP-MAPOP is based on a multi-agent partial order planning paradigm in which agents have diverse abilities, use an argumentation-based defeasible reasoning to support their own beliefs and refute the beliefs of the others according to their knowledge during the plan search process. The requirements of Ambient Intelligence (AmI) environments featured by the imperfect nature of the context information and heterogeneity of the involved agents make defeasible argumentation be an ideal approach to resolve potential conflicts caused by the contradictory information coming from the ambient agents. Moreover, the ability of AmI systems to build a course of action to achieve the user's needs is also a claiming capability in such systems. DeLP-MAPOP shows to be an adequate approach to tackle AmI problems as it gathers together in a single framework the ability of planning while it allows agents to put forward arguments that support or argue upon the accuracy, unambiguity and reliability of the context-aware information.