Book contents
- Frontmatter
- Dedication
- Contents
- List of Algorithms
- Table of Notation
- Foreword
- Preface
- 1 Introduction
- 2 Deliberation with Deterministic Models
- 3 Deliberation with Refinement Methods
- 4 Deliberation with Temporal Models
- 5 Deliberation with Nondeterministic Models
- 6 Deliberation with Probabilistic Models
- 7 Other Deliberation Functions
- 8 Concluding Remarks
- Appendix A Search Algorithms
- Appendix B Strongly Connected Components of a Graph
- Bibliography
- Index
8 - Concluding Remarks
Published online by Cambridge University Press: 05 August 2016
- Frontmatter
- Dedication
- Contents
- List of Algorithms
- Table of Notation
- Foreword
- Preface
- 1 Introduction
- 2 Deliberation with Deterministic Models
- 3 Deliberation with Refinement Methods
- 4 Deliberation with Temporal Models
- 5 Deliberation with Nondeterministic Models
- 6 Deliberation with Probabilistic Models
- 7 Other Deliberation Functions
- 8 Concluding Remarks
- Appendix A Search Algorithms
- Appendix B Strongly Connected Components of a Graph
- Bibliography
- Index
Summary
In this book, we have studied computational reasoning principles and mechanisms to support choosing and performing actions.Here are some observations about the current status of work on those topics.
Extensive work has been done on automated planning, ranging from classical planning techniques to extended approaches dealing with temporal, hierarchical, nondeterministic, and probabilistic models. The field has progressed tremendously, and a strong community of scientists is continually producing new results, technology, and tools.
Issues related to acting have also attracted much attention, and the state of the art is broad and rich, but it is quite fragmented.The relationships among different approaches have not yet been studied in depth, and a unifying and formal account of acting is not available in the same way as it is in the field of automated planning.
Furthermore, the problems of how to generate plans and how to perform synthesized actions have been mainly studied separately, and a better understanding is needed of the relationships between planning and acting. One of the usual assumptions in research on planning is that actions are directly executable, and this assumption is used even in the work on interleaving online planning and execution. In most cases, however, acting cannot be reduced to the direct execution of atomic commands that have been chosen by a planner. Significant deliberation is needed for an actor to perform what is planned.
In this book, we have addressed the state of the art from a unifying perspective.We have presented techniques for doing planning with deterministic,hierarchical, temporal, nondeterministic, and probabilistic models, and have discussed approaches for reacting to events and refining actions into executable commands. In doing this, we have distinguished between two kinds of models:
• Descriptivemodels of actions specify the actor's “know what.”They describe which state or set of possible statesmay result from performing an action.They are used by the actor to reason about which actions may achieve its objectives.
• Operational models of actions specify the actor's “know how.” They describe how to perform an action, that is,what commands to execute in the current context and how to organize them to achieve the action's intended effects. The actor relies on operational models to perform the actions that it has decided to perform.
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- Automated Planning and Acting , pp. 310 - 312Publisher: Cambridge University PressPrint publication year: 2016