Bias in Planning and Explanation-Based Learning

Publisher Summary This chapter discusses bias in planning and explanation-based learning. Bias is any basis for choosing one generalization over another, other than strict consistency with the observed training instances. One has taken seriously the notion of bias as a means of characterizing variations among planners. It is hypothesized that this would yield three benefits: (1) help organize and understand many of the concepts in planning, (2) reduce the computational requirements of planning, and (3) induce effective biases in learning. The first benefit has not yet led to a complete theory or taxonomy of planning methods, but it has led to the development of several orthogonal bias dimensions that provide fragments of organization over the space of methods. Regarding the second benefit, initial experiments with the six planners suggest monotonie trade-offs between completeness and efficiency as the bias dimensions are traversed from least to most restrictive. On the third benefit, the effects of changes in planning bias on bias in explanation-based learning were investigated with a case study in generalization to N.