Recent developments have clarified the process of generating partially ordered, partially
specified sequences of actions whose execution will achieve an agent's goal. This article …

We define the probabilistic planning problem in terms of a probability distribution over initial
world states, a boolean combination of propositions representing the goal, a probability …

Most research into applying AI techniques to real-time control problems has limited the
power of AI methods or embedded reactivity in an AI system. An alternative, cooperative …

The methodological underpinnings of AI are slowly changing. Benchmarks, test beds, and
controlled experimentation are becoming more common. Although we are optimistic that this …

RPL (Reactive Plan Language) 1 belongs to the family of notations for writing reactive plans
for agents (eg, robots)(Davis 1984, Ingrand and George 1990, Lyons 1990a, b, Gat 1991). Its …

This paper presents an algorithm, called Just-In-Case Schedulkg, for building robust
schedules that tend not to break. The algorithm implements the common sense idea of being …

Research on planning for robots is in such a state of flux that there is disagreement about
what planning is and whether it is necessary. We can take planning to be the optimization …

This dissertation demonstrates that effective control of autonomous mobile robots in real-
world environments can be achieved by combining reactive and deliberative components …

AI planning agents are goal‐directed: success is measured in terms of whether an input goal
is satisfied. The goal gives structure to the planning problem, and planning representations …

As intelligent, autonomous systems are embedded in critical real-world environments, it
becomes increasingly important to rigorously characterize how these systems will perform …