Complexity, decidability and undecidability results for domain-independent planning
Complexity, decidability and undecidability results for domain-independent planning
Partial constraint satisfaction
Artificial Intelligence - Special volume on constraint-based reasoning
Fast planning through planning graph analysis
Artificial Intelligence
Fast planning through greedy action graphs
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
State-space planning by integer optimization
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
CPlan: a constraint programming approach to planning
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Using global constraints for local search
DIMACS workshop on on Constraint programming and large scale discrete optimization
Scaling up Planning by Teasing out Resource Scheduling
ECP '99 Proceedings of the 5th European Conference on Planning: Recent Advances in AI Planning
Numeric State Variables in Constraint-Based Planning
ECP '99 Proceedings of the 5th European Conference on Planning: Recent Advances in AI Planning
The LPSAT engine & its application to resource planning
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
To encode or not to encode-1: linear planning
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Planning with sharable resource constraints
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Pushing the envelope: planning, propositional logic, and stochastic search
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
A cost-directed planner: preliminary report
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Planning by rewriting: efficiently generating high-quality plans
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Meta-heuristics: The State of the Art
ECAI '00 Proceedings of the Workshop on Local Search for Planning and Scheduling-Revised Papers
Answer Set Planning under Action Costs
JELIA '02 Proceedings of the European Conference on Logics in Artificial Intelligence
Multiobjective heuristic state-space planning
Artificial Intelligence
An agent model for fault-tolerant systems
Proceedings of the 2005 ACM symposium on Applied computing
Lecture Notes in Computer Science
Answer set planning under action costs
Journal of Artificial Intelligence Research
Multi-unit tactical pathplanning
CIG'09 Proceedings of the 5th international conference on Computational Intelligence and Games
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Resources such as food, hit points or magical power are standard features of today's computer games. Computer-guided characters often have goals that are related to these resources and must take this into account in planning their behavior. In the field of artificial intelligence, resource-based action planning systems have recently begun to mushroom. However, these systems still tend to neglect resources. Conventional plan length is the primaryoptimization goal, resources being of onlysecondaryimp ortance. This paper illustrates the problem and gives an overview of the EXCALIBUR agent's planning system, which overcomes these deficiencies byapply ing an extended constraint programming framework to planning. It allows the search space to be explored without the need to focus on plan length, makes it possible to optimize other criteria like resource-related properties and promotes the inclusion of domain-dependent knowledge to guide and accelerate the search for a plan.