Encoding domain knowledge for prositional planning
Logic-based artificial intelligence
TALplanner: A temporal logic based forward chaining planner
Annals of Mathematics and Artificial Intelligence
Replanning in a Resource-Based Framework
Proceedings of the 9th ECCAI-ACAI/EASSS 2001, AEMAS 2001, HoloMAS 2001 on Multi-Agent-Systems and Applications II-Selected Revised Papers
LPNMR '01 Proceedings of the 6th International Conference on Logic Programming and Nonmonotonic Reasoning
Constraint partitioning in penalty formulations for solving temporal planning problems
Artificial Intelligence
Domain-dependent knowledge in answer set planning
ACM Transactions on Computational Logic (TOCL)
Managing concurrency in temporal planning using planner-scheduler interaction
Artificial Intelligence
TALplanner in the third international planning competition: extensions and control rules
Journal of Artificial Intelligence Research
Temporal planning using subgoal partitioning and resolution in SGPlan
Journal of Artificial Intelligence Research
Planning with resources and concurrency a forward chaining approach
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Hybrid STAN: Identifying and managing combinatorial optimisation sub-problems in planning
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
A temporal logic-based planning and execution monitoring framework for unmanned aircraft systems
Autonomous Agents and Multi-Agent Systems
Constraint partitioning in penalty formulations for solving temporal planning problems
Artificial Intelligence
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We present a new forward chaining planner, TALplanner, based on ideas developed by Bacchus [5] and Kabanza [11], where domain-dependent search control knowledge represented as temporal formulas is used to effectively control forward chaining. Instead of using a linear modal tense logic as with Bacchus and Kabanza, we use TAL, a narrative-based linear temporal logic used for reasoning about action and change in incompletely specified dynamic environments. Two versions of TALplanner are considered, TALplan/modal which is based on the use of emulated modal formulas and a progression algorithm, and TALplan/non-modal which uses neither modal formulas nor a progression algorithm. For both versions of TALplanner and for all tested domains, TALplanner is shown to be considerably faster and requires less memory. The TAL versions also permit the representation of durative actions with internal state.