Open AccessProceedings Article
Planning in a hierarchy of abstraction spaces
Earl D. Sacerdott
- pp 412-422
Reads0
Chats0
TLDR
Examples of the ABSTRIPS system's performance are presented that demonstrate the significant increases in problem-solving power that this approach provides, and some further implications of the hierarchical planning approach are explored.Abstract:
A problem domain can be represented as a hierarchy of abstraction spaces in which successively finer levels of detail are introduced. The problem sotver ABSTRIPS, a modification of STRIPS, can define an abstraction space hierarchy from the STRIPS representatien of a problem domain, and it can utilize the hierarchy in solving problems. Examples of the system's performance are presented that demonstrate the significant increases in problem-solving power that this approach provides. Then some further implications of the hierarchical planning approach are explored.read more
Citations
More filters
Journal ArticleDOI
The multiple-demand (MD) system of the primate brain: mental programs for intelligent behaviour.
TL;DR: FMRI data indicate a key role for MD cortex in defining and controlling the parts of such programs, with focus on the specific content of a current cognitive operation, rapid reorganization as mental focus is changed, and robust separation of successive task steps.
Journal ArticleDOI
Analyzing intention in utterances
James F. Allen,C. R. Perrault +1 more
TL;DR: It is shown that, given a setting in which purposeful dialogues occur, this model of cooperative behavior can account for responses that provide more information that explicitly requested and for appropriate responses to both short sentence fragments and indirect speech acts.
Proceedings Article
AND/OR graph representation of assembly plans
TL;DR: A compact representation of all possible assembly plans of a given product using AND/OR graphs is presented, which forms the basis for efficient planning algorithms which enable an increase in assembly system flexibility by allowing an intelligent robot to pick a course of action according to instantaneous conditions.
Proceedings Article
Systematic nonlinear planning
TL;DR: A simple, sound, complete, and systematic algorithm for domain independent STRIPS planning by starting with a ground procedure and then applying a general, and independently verifiable, lifting transformation.
Journal ArticleDOI
AND/OR graph representation of assembly plans
TL;DR: A compact representation of all possible assembly plans of a given product using AND/OR graphs is presented in this article, which forms the basis for efficient planning algorithms that make possible an increase in assembly system flexibility by allowing an intelligent robot to pick a course of action according to instantaneous conditions.
References
More filters
Book ChapterDOI
Some philosophical problems from the standpoint of artificial intelligence
TL;DR: In this paper, the authors consider the problem of reasoning about whether a strategy will achieve a goal in a deterministic world and present a method to construct a sentence of first-order logic which will be true in all models of certain axioms if and only if a certain strategy can achieve a certain goal.
Journal ArticleDOI
Strips: A new approach to the application of theorem proving to problem solving
Richard Fikes,Nils J. Nilsson +1 more
TL;DR: In this paper, the authors describe a problem solver called STRIPS that attempts to find a sequence of operators in a space of world models to transform a given initial world model in which a given goal formula can be proven to be true.
Book
How to Solve It
TL;DR: Here is a familiar problem having the same or similar unknwn form and here is a problem similar to yours and solved before.
Journal ArticleDOI
Learning and executing generalized robot plans
TL;DR: Some major new additions to the STRIPS robot problem-solving system are described, including a process for generalizing a plan produced by STriPS so that problem-specific constants appearing in the plan are replaced by problem-independent parameters.