Type System Based Rational Lazy IDA*

Meta-reasoning can improve numerous search algorithms, but necessitates collection of statistics to be used as probability distributions, and involves restrictive meta-reasoning assumptions. The recently suggested scheme of type systems in search algorithms is used in this paper for collecting these statistics. The statistics are then used to better estimate the unknown quantity of expected regret of computing a heuristic in Rational Lazy IDA* (RLIDA*), and also facilitate a second improvement due to relaxing one of the unrealistic meta-reasoning assumptions in RLIDA*