We present a general constraint-based encoding for domain-independent task planning.
Task planning is characterized by causal relationships expressed as conditions and effects …

Planning for and controlling a network of interacting devices requires a planner that
accounts for the automatic timed transitions of devices, while meeting deadlines and …

We propose revisions to the research agenda in Automated Planning. The proposal is
based on a review of the role of the Planning Domain Definition Language (PDDL) in the …

Temporal planning is a hard problem that requires good heuristic and memoization
strategies to solve efficiently. Merge-and-shrink abstractions have been shown to serve as …

Computation of invariants, which are approximate reachability information for state-space
search problems such as AI planning, has been considered to be more scalable when using …

The field of AI planning has seen rapid progress over the last decade and planners are now
able to find plan with hundreds of actions in a matter of seconds. Despite those important …

In this dissertation I develop a deep theory of temporal planning well-suited to analyzing,
understanding, and improving the state of the art implementations (as of 2012). At face-value …

In this work we present a new lifted forward-chaining planning system which uses new
heuristics and introduces novel pruning techniques which can solve problem instances …

Automatically identified invariants are an important part of reductions of state-space
reachability problems to SAT and related formalisms as a method of pruning the search …

We present a technique for automatically extracting mutual exclusion invariants from
temporal planning instances. It first identifies a set of invariant templates by inspecting the …