The document discusses Adaptable Constrained Genetic Programming (ACGP), which aims to automate the discovery of heuristics to guide the genetic programming search. It describes how ACGP develops first-order and second-order heuristics based on patterns observed in high-performing individuals, and uses these heuristics to bias mutation, crossover and regrowth. Experimental results on a target equation with explicit second-order structure show that ACGP with second-order heuristics outperforms both standard GP and ACGP with only first-order heuristics. The document concludes that ACGP is effective at discovering and exploiting problem structure through its adaptive heuristic approach.