Foundations of logic programming
Principles of knowledge representation
Argumentation and Decision Making: A Position Paper
FAPR '96 Proceedings of the International Conference on Formal and Applied Practical Reasoning
Argumentation based decision making for autonomous agents
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Defeasible logic programming: an argumentative approach
Theory and Practice of Logic Programming
Using arguments for making decisions: a possibilistic logic approach
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Explaining qualitative decision under uncertainty by argumentation
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Arguing for decisions: a qualitative model of decision making
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Argumentation for decision support
DEXA'06 Proceedings of the 17th international conference on Database and Expert Systems Applications
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
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In this paper we present a model for defeasible decision making that combines decision rules and arguments. In this decision framework we can change the agent's decision policy in a flexible way, with minor changes in the criteria that influence the agent's preferences and the comparison of arguments. Our approach includes a simple methodology for developing the decision components of the agent. A decision framework designed with this methodology exhibits some interesting properties. If the agent (decision maker) has available all the relevant knowledge about its preferences among the different alternatives that could be conceivably posed to it, then our proposal implements a rational preference relation. In opposition, if the agent has partial knowledge about its preferences, the decisions made by the agent still exhibits a behavior consistent with the weak axiom of revealed preference of the choice-based approach, a more flexible approach to Individual Decision Making than the preference-based approach. The principles stated in this work are exemplified in a robotic domain, where a robot should make decisions about which box must be transported next.