Papers by David E Wilkins
Extending artificial intelligence techniques for hierarchical planning
Journal of Computing in Civil Engineering, Oct 1, 1991
Research on Problem-Solving Systems
Hierarchical Planning: Definition and Implementation
Ecai, 1986
... 5 Summary Ambiguities in the planning literature involving hierarchical levels are explicated... more ... 5 Summary Ambiguities in the planning literature involving hierarchical levels are explicated ... The interleaving of planning levels and abstraction levels prevents some current planners ... two methods implemented in SIPE involve different tradeoffs between flexibility, efficiency, and ...
Ijcai, 1983
The representation used in a domain-independent planning program that supports both automatic and... more The representation used in a domain-independent planning program that supports both automatic and interactive generation of hierarchical, partially ordered plans is described. An improved formalism for representing domains and actions is presented. The formalism makes extensive use of constraints, offers efficient methods for representing properties of objects that do not change over time, allows specification of plan rationale, allows specification of resources for efficiently detecting and remedying harmful parallel interactions, and provides the ability to express deductive rules for deducing the effects of actions.
Practical Planning: Extending the Classical Ai Planning Paradigm Morgan Kaufmann Publishers
Page 1. PRACTICAL PLANNING EXTENDING THE CLASSICAL AI PLANNING PARADIGM DAVID E. WILKINS Page 2. ... more Page 1. PRACTICAL PLANNING EXTENDING THE CLASSICAL AI PLANNING PARADIGM DAVID E. WILKINS Page 2. Page 3. Page 4. Page 5. Practical Planning: Extending the Classical AI Planning Paradigm Page 6. The MORGAN ...
Research on Parallelism in Problem-Solving Systems
We briefly describe the history of ARPI projects at SRI International. Our work on agents situate... more We briefly describe the history of ARPI projects at SRI International. Our work on agents situated in dynamic and unpredictable environments is described in more detail. Such agents require several capabili-ties for successful operation, such as monitoring the world, responding appropriately to important events, accepting goals, synthesizing plans for achieving those goals, and executing the plans while continuing to be responsive to changes in the world. In addition, the agents should be able to replan as changes in the world render their plans obsolete, and to reason about un-certain information. The Cypress system is a domain-independent framework for defining persistent agents with this full range of behavior and has been used for several demanding applications, including military op-erations, real-time tracking and fault diagnosis. The Cypress technology will be incorporated in the Multi-agent Planning Architecture, currently under develop-ment, which will provide a new archite...
The Act Formalism
This document describes Version 2.2 of SRI's Act formalism. The Act formalism is a domain-ind... more This document describes Version 2.2 of SRI's Act formalism. The Act formalism is a domain-independent language for representing task networks whose actions manipulate both an external world and an internal database. It is intended to serve as an interchange language that will enable a broad range of action-related technologies to share information. The most recent version of the Act specification can be found at the URL: http://www.ai.sri.com/act/act-spec.ps
The Act-Editor User's Guide
This document describes the Act-Editor, which provides a graphical user interface for creating an... more This document describes the Act-Editor, which provides a graphical user interface for creating and manipulating Acts. The document is designed for individuals who are already familiar with the Act formalism [7]. The Act-Editor runs on Sun workstations with either Allegro Common Lisp 4.2/4.3 with CLIM 2.0/2.1, or Lucid Lisp 4.1 with CLIM 1.1, as well as Symbolics Lisp Machines.
The Current and Future Role of Chess in Artificial Intelligence an Machine Learning
Our great researchers John McCarthy, Allen Newell, Claude Shannon and Herb Simon, Ken Thompson an... more Our great researchers John McCarthy, Allen Newell, Claude Shannon and Herb Simon, Ken Thompson and Alan Turing have each put significant effort into computer chess research. It seems that now that computers have reached the grandmaster level and are beginning to vie for the World Championship the AI community should pause to evaluate what significance chess has to the evolving objectives of AI, what contributions have been made to date, and what can be expected in the future. Despite the general interest in chess amongst computer scientists and the significant progress in the last twenty years, there seems to be a lack of appreciation for the field in the AI community. On one hand this is the fruit of success (brute force works, why work on anything else?), but also the result of a focus on performance above all else in the chess community. Also, chess has proved to be too challenging for many of the AI techniques that have been thrown at it. We wish to promote chess as the unique t...
International Conference on Automated Planning and Scheduling/Artificial Intelligence Planning Systems, 1998
The Multiagent Planning Architecture (MPA) is a framework for integrating diverse technologies in... more The Multiagent Planning Architecture (MPA) is a framework for integrating diverse technologies into a system capable of solving complex planning prob- lems. Agents within MPA share well-defined, uni- form interface specifications that facilitate integration of new technologies and experimentation with differ- ent problem-solving strategies. MPA provides a cen- tral repository for storing plan-related information in a shared plan representation, and
This paper describes a prototype system for quickly developingjoint military courses of action. T... more This paper describes a prototype system for quickly developingjoint military courses of action. The system, SOCAP (System for OperationsCrisis Action Planning), combines a newly extended versionof an AI planning system, SIPE--2 (System for Interactive Planningand Execution), with a color map display and applies this technologyto military operations planning. This paper describes the Socap problemdomain, how SIPE--2 was used to address
Practical planning - extending the classical AI planning paradigm
Page 1. PRACTICAL PLANNING EXTENDING THE CLASSICAL AI PLANNING PARADIGM DAVID E. WILKINS Page 2. ... more Page 1. PRACTICAL PLANNING EXTENDING THE CLASSICAL AI PLANNING PARADIGM DAVID E. WILKINS Page 2. Page 3. Page 4. Page 5. Practical Planning: Extending the Classical AI Planning Paradigm Page 6. The MORGAN ...
International Joint Conference on Artificial Intelligence, 1991
Our eminent researchers including John McCarthy, Allen Newell, Claude Shannon, Herb Simon, Ken Th... more Our eminent researchers including John McCarthy, Allen Newell, Claude Shannon, Herb Simon, Ken Thompson and Alan Turing put significant effort into computer chess research. Now that comput ers have reached the grandmaster level, and are beginning to vie for the World Championship, the AI community should pause to evaluate the sig nificance of chess in the evolving objectives of AI,
A Policy Engine for Spectrum Sharing
2007 2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2007
Using the SIPE-2 Planning System
makesnamed plans out of all abstract partial plans generated while solving a particular problem. ... more makesnamed plans out of all abstract partial plans generated while solving a particular problem. Regroupmakes a new copy of a given plan and adds ordering links to this copy according to an algorithm forregrouping plan actions. Rename renames the current plan and its drawing.The following commands do not generate new plans:Execute --- invokes the execution monitor on the current plan with graphics (see Chapter 6)Execute-any --- invokes the execution monitor on a selected planPrint...
IEEE Wireless Communications, 2000
Computational Intelligence, 1998
Locational reasoning plays an important role in many applications of AI problem-solving systems, ... more Locational reasoning plays an important role in many applications of AI problem-solving systems, yet has remained a relatively unexplored area of research. This paper addresses both theoretical and practical issues relevant to reasoning about locations. We define several theories of location designed for use in various settings, along with a sound and complete belief revision calculus for each that maintains a STRIPS-style database of locational facts. Techniques for the efficient operationalization of the belief revision rules in planning frameworks are presented. These techniques were developed during application of the location theories to several large-scale planning tasks within the SIPE-2 planning framework.
Computational Intelligence, 1988
Reasoning about actions is a pervasive form of human activity. The ability to establish goals and... more Reasoning about actions is a pervasive form of human activity. The ability to establish goals and plan courses of action to achieve them is a prominent characteristic of intelligent behavior. During the last several years, interest in planning research within the artificial intelligence community has been increasing. Areas as diverse as factory automation, natural-language understanding, and mobile robots have recognized the need for planning.
Computational Intelligence, 1990
While there has been recent interest in research on planning and reasoning about actions, nearly ... more While there has been recent interest in research on planning and reasoning about actions, nearly all research results have been theoretical. We know of no previous examples of a planning system that has made a significant impact on a problem of practical importance. One of the primary goals during the development of the SIPE-2 planning system has been the balancing of efficiency with expressiveness and flexibility. With a major new extension, SIPE-2 has begun to address practical problems. This paper describes this new extension and the new applications of the planner. One of these applications is the problem of producing products from raw materials on process lines under production and resource constraints. This is a problem of commercial importance and s l P E -2 '~ application to it is described in some detail.
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Papers by David E Wilkins