Using Temporal Logic to Integrate Goals and Qualitative Preferences into Agent Programming
Declarative Agent Languages and Technologies VI
Anytime heuristic search for partial satisfaction planning
Artificial Intelligence
Agent programming with temporally extended goals
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
An argumentation-based interpreter for Golog programs
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Scheduling with soft constraints
Proceedings of the 2009 International Conference on Computer-Aided Design
CPP: a constraint logic programming based planner with preferences
LPNMR'07 Proceedings of the 9th international conference on Logic programming and nonmonotonic reasoning
Planning for multiagent using ASP-prolog
CLIMA'09 Proceedings of the 10th international conference on Computational logic in multi-agent systems
Specifying and computing preferred plans
Artificial Intelligence
Argumentation-based negotiation planning for autonomous agents
Decision Support Systems
Perspectives on logic-based approaches for reasoning about actions and change
Logic programming, knowledge representation, and nonmonotonic reasoning
Answer set general theories and preferences
MICAI'06 Proceedings of the 5th Mexican international conference on Artificial Intelligence
Web service composition via generic procedures and customizing user preferences
ISWC'06 Proceedings of the 5th international conference on The Semantic Web
Reasoning and planning with cooperative actions for multiagents using answer set programming
DALT'09 Proceedings of the 7th international conference on Declarative Agent Languages and Technologies
Generating diverse plans to handle unknown and partially known user preferences
Artificial Intelligence
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We present a declarative language, ${\cal PP}$, for the high-level specification of preferences between possible solutions (or trajectories) of a planning problem. This novel language allows users to elegantly express non-trivial, multi-dimensional preferences and priorities over such preferences. The semantics of ${\cal PP}$ allows the identification of most preferred trajectories for a given goal. We also provide an answer set programming implementation of planning problems with ${\cal PP}$ preferences.