A Language for Planning with Statistics

TL;DR

This paper introduces an event-based language for planning that calculates probabilities from observed event ratios using statistical inference, enabling planners to assess evidence strength and validity of their decisions.

Contribution

It presents a novel language integrating statistical inference into planning, allowing probability calculations from observed data and validity checks via interval estimation.

Findings

Probabilities are derived from observed event ratios.

Interval estimation helps assess the validity of probabilities.

The approach enables more reliable decision-making in planning.

Abstract

When a planner must decide whether it has enough evidence to make a decision based on probability, it faces the sample size problem. Current planners using probabilities need not deal with this problem because they do not generate their probabilities from observations. This paper presents an event based language in which the planner's probabilities are calculated from the binomial random variable generated by the observed ratio of one type of event to another. Such probabilities are subject to error, so the planner must introspect about their validity. Inferences about the probability of these events can be made using statistics. Inferences about the validity of the approximations can be made using interval estimation. Interval estimation allows the planner to avoid making choices that are only weakly supported by the planner's evidence.