Reference - nareyek-98-model

Reference: nareyek-98-model

Reference Nareyek, A. 1998.
A Planning Model for Agents in Dynamic and Uncertain Real-Time Environments.
In Proceedings of the 1998 AIPS Workshop on Integrating Planning, Scheduling and Execution in Dynamic and Uncertain Environments, Technical Report, WS-98-02, 7-14. AAAI Press, Menlo Park, California.

Abstract
The management of an agent in a dynamic and uncertain real-time environment is fairly intractable with traditional planning methods. Such methods cannot be computed efficiently, are not capable of replanning, and mostly lack explicit temporal formalisms. The planning model proposed in this paper overcomes these weaknesses by applying iterative repair methods, constraint-programming techniques, and an explicit timeline approach.

For the management of incomplete knowledge, a single-plan approach is proposed in which only one plan possibility is considered. The application of Unknown values, Known values, Not values, and continuous domain fluents enables to cope with incomplete knowledge.

Download Rules and Regulations [PostScript; 427 Kb] [compressed PostScript; 127 Kb] [download viewer]
Online Content
The article includes content from the AI Center pages below. Please note that the online pages may contain updated/revised versions, and probably do not cover the complete article:

The Model's Basics
Actions, Action Tasks and Action Resources
State Resources, State Tasks and Precondition Tasks
Objects and References
Sensors and Existence
Incomplete Knowledge
A Single-Plan Approach
Missing Information
Information Gathering
Run-Time Variables
Hands-off Goals
Partial Knowledge
Unordered Domains
Ordered Domains
Probabilities

Reference	Nareyek, A. 1998. A Planning Model for Agents in Dynamic and Uncertain Real-Time Environments. In Proceedings of the 1998 AIPS Workshop on Integrating Planning, Scheduling and Execution in Dynamic and Uncertain Environments, Technical Report, WS-98-02, 7-14. AAAI Press, Menlo Park, California.
Abstract	The management of an agent in a dynamic and uncertain real-time environment is fairly intractable with traditional planning methods. Such methods cannot be computed efficiently, are not capable of replanning, and mostly lack explicit temporal formalisms. The planning model proposed in this paper overcomes these weaknesses by applying iterative repair methods, constraint-programming techniques, and an explicit timeline approach. For the management of incomplete knowledge, a single-plan approach is proposed in which only one plan possibility is considered. The application of Unknown values, Known values, Not values, and continuous domain fluents enables to cope with incomplete knowledge.
Download	Rules and Regulations [PostScript; 427 Kb] [compressed PostScript; 127 Kb] [download viewer]
Online Content	The article includes content from the AI Center pages below. Please note that the online pages may contain updated/revised versions, and probably do not cover the complete article: The Model's Basics Actions, Action Tasks and Action Resources State Resources, State Tasks and Precondition Tasks Objects and References Sensors and Existence Incomplete Knowledge A Single-Plan Approach Missing Information Information Gathering Run-Time Variables Hands-off Goals Partial Knowledge Unordered Domains Ordered Domains Probabilities