Recent years has seen intense analysis and questioning of the importance of the role of classical AI-planning in deciding moment-to-moment actions. This has led to development of several new AI-planning paradigms such as reactive planning [Fir87, GL87]. Informally, a planning paradigm refers to principles ofrepresenting an agent's acts, beliefs and expectations about concepts-relatingacts-to-co...

this study examined the effects of aural and written prompts under two planning conditions (i.e. pre-task planning and no planning) on complexity, accuracy, and fluency of test takers' writing production. forty learners in an english institute, who had already been classified as intermediate according to the oxford placement test, were assigned to two planning conditions (i.e. no planning and p...

A new market based approach for transmission expansion planning in deregulated environments is presented in this paper. In this approach, transmission-planning decisions are made based on the electric power market conditions. The main contribution of this research is 1) Introducing a new probabilistic tool for analyzing the electric market conditions, 2) Defining new criteria for ranking transm...

Many software applications consist of a number of interdependent steps and are executed under the supervision of a human administrator or operator. The administrator responds to error conditions and checks to see that the dependencies between steps has been satisfied before allowing the application to continue. AI planning systems, because they have the capability of responding to a dynamically...

Most current-day AI planning systems operate by iteratively refining a partial plan until it meets the goal requirements. In the past five years, significant progress has been made in our understanding of the spectrum and capabilities of such refinement planners. In this talk, I will summarize this understanding in terms of a unified framework for refinement planning and discuss several current...

Derivation replay was first proposed by Carbonell as a method of transferring guidance from a previous problemsolving episode to a new one. Subsequent implementations have used state-space planning as the underlying methodology. This paper is motivated by the acknowledged superiority of partial-order (PO) planners in plan generation, and is an attempt to bring derivation replay into the realm o...

This paper presents three approaches to generate learning designs using existing domain-independent planners. All of the approaches compile a course defined in a standard e-learning language into a planning domain, and a file containing student’s learning information into a planning problem. The learning designs are automatically generated from the plans that solve the problems. The approaches ...

We consider the problem of temporal planning in which a given goal is reached by taking a number of actions which may temporally overlap and interfere, and the interference may be essential for reaching the goals. We formalize a general temporal planning problem, show that its plan existence problem is EXPSPACE-complete, and give conditions under which it is reducible to classical planning and ...

In deep brain stimulation surgeries, stimulating electrodes are placed at specific targets in the deep brain to treat neurological disorders. Reaching these targets safely requires avoiding critical structures in the brain. Meticulous planning is required to find a safe path from the cortical surface to the intended target. Choosing a trajectory automatically is difficult because there is littl...

AI planning techniques are beginning to find use in a number of practical planning domains. However, the backward-chaining and partial-order-planning control strategies traditionally used in AI planning systems are not necessarily the best ones to use for practical planning problems. In this paper, we discuss some of the difficulties that can result from the use of backward chaining and partial...