Efficient, Safe, and Probably Approximately Complete Learning of Action Models

In this paper we explore the theoretical boundaries of planning in a setting where no model of the agent's actions is given. Instead of an action model, a set of successfully executed plans are given and the task is to generate a plan that is safe, i.e., guaranteed to achieve the goal without failing. To this end, we show how to learn a conservative model of the world in which actions are guaranteed to be applicable. This conservative model is then given to an off-the-shelf classical planner, resulting in a plan that is guaranteed to achieve the goal. However, this reduction from a model-free planning to a model-based planning is not complete: in some cases a plan will not be found even when such exists. We analyze the relation between the number of observed plans and the likelihood that our conservative approach will indeed fail to solve a solvable problem. Our analysis show that the number of trajectories needed scales gracefully

FLECS: Planning with a Flexible Commitment Strategy

There has been evidence that least-commitment planners can efficiently handle planning problems that involve difficult goal interactions. This evidence has led to the common belief that delayed-commitment is the "best" possible planning strategy. However, we recently found evidence that eager-commitment planners can handle a variety of planning problems more efficiently, in particular those with difficult operator choices. Resigned to the futility of trying to find a universally successful planning strategy, we devised a planner that can be used to study which domains and problems are best for which planning strategies. In this article we introduce this new planning algorithm, FLECS, which uses a FLExible Commitment Strategy with respect to plan-step orderings. It is able to use any strategy from delayed-commitment to eager-commitment. The combination of delayed and eager operator-ordering commitments allows FLECS to take advantage of the benefits of explicitly using a simulated execution state and reasoning about planning constraints. FLECS can vary its commitment strategy across different problems and domains, and also during the course of a single planning problem. FLECS represents a novel contribution to planning in that it explicitly provides the choice of which commitment strategy to use while planning. FLECS provides a framework to investigate the mapping from planning domains and problems to efficient planning strategies.Comment: See http://www.jair.org/ for an online appendix and other files accompanying this articl

PDDL2.1: An extension of PDDL for expressing temporal planning domains

In recent years research in the planning community has moved increasingly towards application of planners to realistic problems involving both time and many types of resources. For example, interest in planning demonstrated by the space research community has inspired work in observation scheduling, planetary rover ex ploration and spacecraft control domains. Other temporal and resource-intensive domains including logistics planning, plant control and manufacturing have also helped to focus the community on the modelling and reasoning issues that must be confronted to make planning technology meet the challenges of application. The International Planning Competitions have acted as an important motivating force behind the progress that has been made in planning since 1998. The third competition (held in 2002) set the planning community the challenge of handling time and numeric resources. This necessitated the development of a modelling language capable of expressing temporal and numeric properties of planning domains. In this paper we describe the language, PDDL2.1, that was used in the competition. We describe the syntax of the language, its formal semantics and the validation of concurrent plans. We observe that PDDL2.1 has considerable modelling power --- exceeding the capabilities of current planning technology --- and presents a number of important challenges to the research community

An analysis of commitment strategies in planning: The details

We compare the utility of different commitment strategies in planning. Under a 'least commitment strategy', plans are represented as partial orders and operators are ordered only when interactions are detected. We investigate claims of the inherent advantages of planning with partial orders, as compared to planning with total orders. By focusing our analysis on the issue of operator ordering commitment, we are able to carry out a rigorous comparative analysis of two planners. We show that partial-order planning can be more efficient than total-order planning, but we also show that this is not necessarily so

What is a good plan?

The word plan is in English both a verb and a noun, reminding us that to plan is a process resulting in a product, a plan. While the Last Planner System (LPS) is primarily focused on how to plan and control production, other planning concepts are more focused on the plan contents (the plan). A more explicit approach to the characteristics of a good plan could improve LPS as a planning concept. The paper proposes such a list, based on a discussion of the plan contents highlighted by the following planning concepts: Critical Path, the Location-Based Management System, Takt Planning, Critical Chain, Agile, Task Planning and the Last Planner System

Learning our way towards a sustainable agri-food system Three cases from Sweden: Stockholm Farmers market, Ramsjö Community Supported Agriculture and Järna Initiative for Local Production

This research is based on case studies of the Stockholm Farmers Market, Ramsjö Community Supported Agriculture, and Järna Initiative for Local Production. These cases are examples of alternative consumerproducer links in the Swedish agri-food system. An adapted SWOT analysis highlights key strengths, weaknesses, opportunities and constraints in each case from the multiple perspectives of producers, consumers, the organization, as well as the environment and society. Diagrams show where learning opportunities exist in the three systems, and how the structure of the consumer-producer link influences learning processes. Implication assessments consider how each link may affect surrounding ecosystems and social aspects of the agri-food system. A framework for assessing a process of development identifies six components that contribute to agri-food system development. Four key issues are discussed in terms of their potential to significantly affect the development of the agri-food system: the length of the food chain linking producers and consumers, the definition of “local”, learning in the system, and what is really being sold – is it food, or values? Critical research questions are highlighted and recommended for future research

Improving performance through concept formation and conceptual clustering

Research from June 1989 through October 1992 focussed on concept formation, clustering, and supervised learning for purposes of improving the efficiency of problem-solving, planning, and diagnosis. These projects resulted in two dissertations on clustering, explanation-based learning, and means-ends planning, and publications in conferences and workshops, several book chapters, and journals; a complete Bibliography of NASA Ames supported publications is included. The following topics are studied: clustering of explanations and problem-solving experiences; clustering and means-end planning; and diagnosis of space shuttle and space station operating modes