This paper describes the application of Artificial Intelligence planning techniques to the problem of antenna track plan generation for a NASA Deep Space Communications Station. The described system enables an antenna communications station to automatically respond to a set of tracking goals by correctly configuring the appropriate hardware and software to provide the requested communication se...

The paper raises some issues relating to the engineering of domain models for automated planning. It studies the idea of a domain model as a formal specification of a domain, and considers properties of that specification. It proposes some definitions, which the planning and, more generally, the artificial intelligence community needs to consider, in order to properly deal with engineering issu...

In the field of artificial intelligence, ”planning” is defined as designing the behavior of some entity that acts, either an individual, a group, or an organization. The output is some kind of blueprint for behavior, which we call a plan. There are a wide variety of planning problems, differentiated by the types of their inputs and outputs. Typically, planning problems get more and more difficu...

The areas of Artificial Intelligence planning and scheduling have seen important advances thanks to the application of constraint satisfaction models and techniques. Especially, solutions to many real-world problems need to integrate plan synthesis capabilities with resource allocation, which can be efficiently managed by using constraint satisfaction techniques. Constraint satisfaction plays a...

This report documents the outcomes of Dagstuhl Seminar 14032 “Planning with epistemic goals”. It brought together the communities of so far relatively separate research areas related to artificial intelligence and logic: automated planning on the one hand, and dynamic logics of interaction on the other. Significant overlap in motivation, theory and methods was discovered, and a good potential f...

part of the biennial Artificial Intelligence Planning and Scheduling (AIPS) conferences. AIPS’98 featured the very first competition, and for AIPS’00, we built on this foundation to run the second competition. The 2000 competition featured a much larger group of participants and a wide variety of different approaches to planning. Some of these approaches were refinements of known techniques, an...

The Multimodal User Supervised Interface and Intelligent Control (MUSIIC) project is working towards the development of an assistive robotic system which integrates human-computer interaction with reactive planning techniques borrowed from artificial intelligence. The MUSIIC system is intended to operate in an unstructured environment, rather than in a struc-tured workcell, allowing users with ...

Even though reasoning and, in particular, planning techniques have had a long tradition in Artificial Intelligence, these have only recently been applied to interactive computer games. In this paper we propose the use of READYLOG, a variant of the logic-based action language GOLOG, to build game bots. The language combines features from classical programming languages with decision-theoretic pl...

planner in the Fifth International Conference on Artificial Intelligence Planning and Scheduling (AIPS’00) planning systems competition. Like the well-known HSP system, FF relies on forward search in the state space, guided by a heuristic that estimates goal distances by ignoring delete lists. It differs from HSP in a number of important details. This article describes the algorithmic technique...

Reinforcement learning models can explain various aspects of two-way avoidance learning but do not provide a rationale for the relationship found between the dynamics of initial learning and those of reversal learning. Artificial Intelligence planning offers a novel way to conceptualize the learners’ cognitive processes by providing an explicit representation of and reasoning about internal pro...