O-Plan is an AI planner based on previous experience with the Nonlin planner and its derivatives. Nonlin and other similar planning systems had limited control architectures and were only partially successful at limiting their search spaces. O-Plan is a design and implementation of a more flexible system aimed at supporting planning research and development, opening up new planning methods and supporting strong search control heuristics. O-Plan takes an engineering approach to the construction of an efficient domain independent planning system which includes a mixture of AI and numerical techniques from Operations Research. The main contributions of the work are centred around the control of search within the OPlan planning framework, and this paper outlines the search control heuristics employed within the planner. These involve the use of condition typing, time and resource constraints and domain constraints to allow knowledge about an application domain to be used to prune the searc...

This paper describes the O-Plan2 agent oriented architecture and describes the communication which takes place between planning and execution monitoring agents built upon the architecture. Separate modules of such a system are identified along with internal and external interface specifications that form a part of the design. Time constraints, resource usage, object selection and condition/effect causal constraints are handled as an integral part of the overall system structure by treating specialised constraint management as supporting the core decision making components in the architecture. A close coupling of planning and time or resource scheduling is therefore possible within a system employing an activity based plan representation. 2 History and Technical Influences

Explicit causal structure representations have been widely used in classical planning systems to guide a variety of aspects of planning, including plan generation, modification and generalization. For the most part, these representations were limited to single-contributor causal structures. Although widely used, single-contributor causal structures have several limitations in handling partially ordered and partially instantiated plans. The foremost among these is that they are incapable of exploiting redundancy in the plan. In this paper, we explore multi-contributor causal structures as a way of overcoming these limitations. We will provide a general formulation for multi-contributor causal links, and explore the properties of several special classes of this formulation. We will also discuss their applications in plan generation, modification and generalization.

As realistic systems are built and commercial toolkits are created for planning and scheduling applications, it becomes increasingly important that modularisation of these "standard" components is attempted. This can lead to re-usability, embeddability and improved implementation provision. One early example of a standardised component is the Truth Criterion condition establishment algorithm which is now found at the heart of most activity based planning systems. The modularisation of this algorithm has led to an explosion of further development, empirical and theoretical study of this component. The provision of powerful constraint management languages and tools could lead to a rapid expansion of the benefits to be gained by identifying more standard components that can be combined and re-used in planning and scheduling systems. O-Plan2 is a command, planning and control architecture which has an open modular structure intended to allow experimentation on or replacement of various components. This paper describes the modular structure of the system along with the internal and external interface languages and protocols which are being developed on the O-Plan2 project. The research is seeking to isolate functionality that may be generally required in a number of applications and across a number of different planning, scheduling and control systems. This paper is intended to further discussions on the identification of suitable "standard" re-usable components in planning and scheduling systems.

erospace Research and Development by contract number F4962092 -C-0042 (eoard/92-0001) monitored by Northrup Fowler iii at the usaf Rome Laboratory. Additional resources for the O-Plan and O-Plan projects have been provided by the Artificial Intelligence Applications Institute through the europa (Edinburgh University Research on Planning Architectures) institute development project. From 1989 to 1993, research on scheduling applications of the O-Plan architecture was funded by Hitachi Europe Ltd. From 1989 to 1992, the uk Science and Engineering Research Council (grant number gr/f36545 -- uk Information Engineering Directorate project number ied 4/1/1320) funded a collaborative project with icl, Imperial College and other partners in which the O-Plan architecture was used to guide the design and development of a planner with a flexible tempora