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SIPE-2: System for Interactive Planning and Execution

SIPE-2: System for Interactive Planning and Execution   Point of Contact:  Dr David E Wilkins

Mailing address:
AI Center
SRI International
333 Ravenswood Avenue
Menlo Park, CA 94025-3493

Home page at http://www.ai.sri.com/~sipe/

   Software Description

Artificial Intelligence (AI) planning techniques developed over the past three decades at the AI Center of SRI International have now reached the point where they can impact real problems. SIPE-2 is the most advanced of SRI’s plan generation and execution systems, and has been employed by numerous users to solve a range of interesting problems, as described above. It is the planner in the Cypress and CPEF systems and is used in the Multiagent Planning Architecture. SIPE-2 is a performance-oriented, general-purpose software system for generating and monitoring the execution of plans. It plans hierarchically, using different levels of abstraction, and provides a formalism for describing actions as operators. Given an arbitrary initial situation and a set of goals, SIPE-2 either automatically or under interactive control combines operators to generate plans to achieve the prescribed goals in the given world. In contrast to most AI planning research, heuristic adequacy (efficiency) has been one of the primary goals in the design of SIPE-2, which includes many heuristics for reducing computational complexity. Unlike expert systems, the SIPE-2 architecture is capable of generating a novel sequence of actions that responds precisely to the situation at hand. Planning requires the system to predict how the world will change as actions are performed. However, in real-world domains, things do not always proceed as planned and it becomes increasingly important to use as much as possible of the old plan when new situations arise. SIPE-2 has execution-monitoring techniques that accept new information about the world and modify the plan minimally to respond to unexpected events.

   Developers

Name Title E-mail
Lee, Tom J Senior Research Engineer
Myers, Karen Program Director & Principal Scientist
Wilkins, David E Senior Computer Scientist

   Associated Projects
Advisable Planners

Advisable Planners
The Advisable Planners project sought to make AI planning technology more accessible and controllable through the metaphor of advisability. User-provided advice specifies characteristics for both the desired solution and the problem-solving process to be employed during plan generation. Such advice is specified in a high-level language that is natural and intuitive for users, then operationalized into constraints that direct the underlying planning technology.

JFACC Continuous Planning

JFACC Continuous Planning and Execution
The main result of this project was the development of the Continuous Planning and Execution Framework (CPEF), which provides plan generation and replanning capabilities for situated agents in highly dynamic environments. Within CPEF, plans are treated as dynamic, open-ended artifacts that evolve in response to an ever-changing environment. In particular, plans must be updated in response to new information and requirements in a timely fashion to ensure their relevance and viability.

MPA

Multiagent Planning Architecture
MPA is an open planning architecture that facilitates incorporation of new plan-related technologies, capitalizing on the benefits of distributed computing for efficiency and robustness. MPA provides protocols to support the sharing of knowledge and capabilities among agents involved in cooperative problem solving. MPA has been demonstrated in the air campaign planning domain, and was used as the infrastructure for the flagship demonstration of the DARPA Planning Initiative.

SUO-PDA

Planning and Decision Aids for Small Unit Operations
We developed a planning and decision aid (PDA) for the DARPA Small Unit Operations (SUO) program, to show the feasibility of using advanced planning technologies in SUO. The PDA monitors the execution of machine-understandable plans, using events as they are realistically reported in the battlespace, and alerts the user when the situation requires his attention.

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