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Found 13 papers, 3 papers with code
Solving Novel Program Synthesis Problems with Genetic Programming using Parametric Polymorphism
Contemporary genetic programming (GP) systems for general program synthesis have been primarily concerned with evolving programs that can manipulate values from a standard set of primitive data types and simple indexed data structures.
Analyzing the Interaction Between Down-Sampling and Selection
We verified that down-sampling can benefit the problem-solving success of both fitness-proportionate and tournament selection.
A Static Analysis of Informed Down-Samples
We present an analysis of the loss of population-level test coverage induced by different down-sampling strategies when combined with lexicase selection.
Informed Down-Sampled Lexicase Selection: Identifying productive training cases for efficient problem solving
Random down-sampled lexicase selection evaluates individuals on only a random subset of the training cases allowing for more individuals to be explored with the same amount of program executions.
Lexicase Selection at Scale
Lexicase selection is a semantic-aware parent selection method, which assesses individual test cases in a randomly-shuffled data stream.
Functional Code Building Genetic Programming
General program synthesis has become an important application area for genetic programming (GP), and for artificial intelligence more generally.
The Environmental Discontinuity Hypothesis for Down-Sampled Lexicase Selection
Although this down-sampling procedure has been shown to significantly improve performance across a variety of problems, it does not seem to do so due to encouraging adaptability through environmental change.
Population Diversity Leads to Short Running Times of Lexicase Selection
In this paper we investigate why the running time of lexicase parent selection is empirically much lower than its worst-case bound of O(N*C).
Problem-solving benefits of down-sampled lexicase selection
Lexicase selection, by contrast, selects on the basis of performance on random sequences of training cases; this has been shown to enhance problem-solving power in many circumstances.
PSB2: The Second Program Synthesis Benchmark Suite
In this paper, we describe the 25 new general program synthesis benchmark problems that make up PSB2, a new benchmark suite.
Lexicase Selection of Specialists
Lexicase parent selection filters the population by considering one random training case at a time, eliminating any individuals with errors for the current case that are worse than the best error in the selection pool, until a single individual remains.
Comparing and Combining Lexicase Selection and Novelty Search
Lexicase selection and novelty search, two parent selection methods used in evolutionary computation, emphasize exploring widely in the search space more than traditional methods such as tournament selection.
A probabilistic and multi-objective analysis of lexicase selection and epsilon-lexicase selection
Lexicase selection is a parent selection method that considers training cases individually, rather than in aggregate, when performing parent selection.
