Titlebook: Learning Search Control Knowledge; An Explanation-Based Steven Minton Book 1988 Kluwer Academic Publishers, Boston 1988 control.intelligenc

艺术

Introduction,lem solving systems. In practice, a general problem solving system. must be given enough information about the problem and how to solve it so that its search is restricted to a tractable space. Unfortunately, it is typically time-consuming and difficult for a human to provide such information.

吞没

Overview of the PRODIGY Problem Solver,he problem solving architecture in enough detail so that the learning system and its effects can be properly understood. Special emphasis is given to those aspects of the problem solver that are particularly relevant to this thesis.

干涉

Figate

chisel

火海

Learning from Failure,iven strategy described in the previous chapter. Following the outline established in the previous chapter, a description of the strategy will first be provided, followed by several illustrative examples. The chapter will conclude with a description of some of the factors that influence the utility

恶名声

Learning from Goal Interactions, when solving one goal makes a second goal easier to solve; this is generally termed .. Similarly, detrimental goal interactions happen when solving one goal makes a second goal harder to achieve; this case is referred to as ..

雇佣兵

admission

Related Work,earch on explanation-based learning methods and related approaches. In this chapter I review this research and briefly describe its historical development, focusing on the aspects most relevant to this dissertation. For each learning method I will consider two questions: “For what types of problem s

乐器演奏者

Conclusion,deoff effects the utility of learning. The primary claim, or the “thesis of the thesis”, is that a learning system must be sensitive to the knowledge/search tradeoff if it is to have a positive influence on performance. Figure 13–1, adapted from Ebeling [22], graphically illustrates the prototypical