Recently, several planners have been designed that can create conditionally branching plans to solve problems which involve uncertainty. These planners represent an important step in broadening the applicability of AI planning techniques, but they typically must search a larger space than non-branching planners, since they must produce valid plans for each branch considered. In the worst case t...

Recently, several planners have been designed that can create conditionally branching plans to solve problems which involve uncertainty. These planners represent an important step in broadening the applicability of AI planning techniques, but they typically must search a larger space than non-branching planners, since they must produce valid plans for each branch considered. In the worst case t...

A number of current planners make use of automatic domain analysis techniques to extract information such as state invariants or necessary goal orderings from a planning domain. There are also planners that allow the user to explicitly specify additional information intended to improve performance. One such planner is TALplanner, which allows the use of domain-dependent temporal control formula...

This paper explores how applying psychological and cognitive theories in nudge design can increase the effectiveness of nudging public space. Nudges are those policy instruments that alter human behaviour by exploiting biases/heuristics, without limiting choice set. Based on interviews with Dutch urban planners, barriers such behavioural identified. These relate both to planners’ inexperience o...

The main paradigm for practical motion planning in the last two decades is Probabilistic Road Map (PRM). We propose an alternative paradigm called Soft Subdivision Search (SSS). The SSS approach is based on two ingredients: the standard subdivision of space, coupled with soft predicates. Such predicates are conservative and convergent relative to exact predicates. This leads to a new class of r...

A generic planning system is introduced which allows for custom building of planners able to generate plans for diierent plan consumers in the context of intelligent assistance systems. All planners are adapted to the peculari-ties of diierent plan consumers, to their domain knowledge, their typical behavior, their preferences, and their utilization of plans. The necessary knowledge sources of ...

A framework is proposed for the investigation of planning systems that must deal with bounded uncertainty. A deenition of this new class of contingency planners is given. A general, complete contingency planning algorithm is described. The algorithm is suitable to many incomplete information games as well as planning situations where the initial state is only partially known. A rich domain is i...

Many real-world planning problems require generating plans that maximize the parallelism inherent in a problem. There are a number of partial-order planners that generate such plans; however, in most of these planners it is unclear under what conditions the resulting plans will be correct and whether the plaltner can even find a plan if one exists. This paper identifies the underlying assumptio...

Over the years increasingly sophisticated planning algorithms have been developed. These have made for more efficient planners, but unfortunately these planners still suffer from combinatorial explosion. Indeed, recent theoretical results demonstrate that such an explosion is inevitable. It has long been acknowledged that domain independent planners need domain dependent information to help the...

Recent progress in planning has enabled this technique to be applied to some significant real-world problems, including the construction of intelligent user interfaces. Previous research in interactive planners has emphasised their dynamism and maintenance advantages. This paper adopts a user-interaction perspective, and explores the theme that a paradigm shift in human-computer interaction is ...