Foundations of logic programming
Principles of knowledge representation
The BOID architecture: conflicts between beliefs, obligations, intentions and desires
Proceedings of the fifth international conference on Autonomous agents
A Reasoning Model Based on the Production of Acceptable Arguments
Annals of Mathematics and Artificial Intelligence
Explanations, belief revision and defeasible reasoning
Artificial Intelligence
Defeasible logic programming: an argumentative approach
Theory and Practice of Logic Programming
An argumentation based approach for practical reasoning
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
An argumentation based approach for practical reasoning
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
g-BDI: A Graded Intensional Agent Model for Practical Reasoning
MDAI '09 Proceedings of the 6th International Conference on Modeling Decisions for Artificial Intelligence
Defeasible argumentation support for an extended BDI architecture
ArgMAS'07 Proceedings of the 4th international conference on Argumentation in multi-agent systems
An argumentation-based BDI personal assistant
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part I
Query-based argumentation in agent programming
IBERAMIA'10 Proceedings of the 12th Ibero-American conference on Advances in artificial intelligence
TAFA'11 Proceedings of the First international conference on Theory and Applications of Formal Argumentation
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Here, we define a framework where defeasible argumentation is used for reasoning about beliefs, desires and intentions. A dialectical filtering process is introduced to obtain a subset of the agent's desires containing only those that are achievable in the current situation. Different agents types can be defined in the framework affecting the way in which current desires are obtained. The agent is provided with a set of intention rules that specifies under what conditions an intention could be achieved. When more than one intention is present, a policy will be used to choose among them. Thus, intention policies provide the agent with a mechanism for deciding which intention is selected in the current situation. Several application examples will be given.