631 research outputs found
Semantically-based crossover in genetic programming: application to real-valued symbolic regression
We investigate the effects of semantically-based crossover operators in genetic programming, applied to real-valued symbolic regression problems. We propose two new relations derived from the semantic distance between subtrees, known as semantic equivalence and semantic similarity. These relations are used to guide variants of the crossover operator, resulting in two new crossover operators—semantics aware crossover (SAC) and semantic similarity-based crossover (SSC). SAC, was introduced and previously studied, is added here for the purpose of comparison and analysis. SSC extends SAC by more closely controlling the semantic distance between subtrees to which crossover may be applied. The new operators were tested on some real-valued symbolic regression problems and compared with standard crossover (SC), context aware crossover (CAC), Soft Brood Selection (SBS), and No Same Mate (NSM) selection. The experimental results show on the problems examined that, with computational effort measured by the number of function node evaluations, only SSC and SBS were significantly better than SC, and SSC was often better than SBS. Further experiments were also conducted to analyse the perfomance sensitivity to the parameter settings for SSC. This analysis leads to a conclusion that SSC is more constructive and has higher locality than SAC, NSM and SC; we believe these are the main reasons for the improved performance of SSC
On Structural Parameterizations of Hitting Set: Hitting Paths in Graphs Using 2-SAT
Hitting Set is a classic problem in combinatorial optimization. Its input
consists of a set system F over a finite universe U and an integer t; the
question is whether there is a set of t elements that intersects every set in
F. The Hitting Set problem parameterized by the size of the solution is a
well-known W[2]-complete problem in parameterized complexity theory. In this
paper we investigate the complexity of Hitting Set under various structural
parameterizations of the input. Our starting point is the folklore result that
Hitting Set is polynomial-time solvable if there is a tree T on vertex set U
such that the sets in F induce connected subtrees of T. We consider the case
that there is a treelike graph with vertex set U such that the sets in F induce
connected subgraphs; the parameter of the problem is a measure of how treelike
the graph is. Our main positive result is an algorithm that, given a graph G
with cyclomatic number k, a collection P of simple paths in G, and an integer
t, determines in time 2^{5k} (|G| +|P|)^O(1) whether there is a vertex set of
size t that hits all paths in P. It is based on a connection to the 2-SAT
problem in multiple valued logic. For other parameterizations we derive
W[1]-hardness and para-NP-completeness results.Comment: Presented at the 41st International Workshop on Graph-Theoretic
Concepts in Computer Science, WG 2015. (The statement of Lemma 4 was
corrected in this update.
Quantitative Models and Implicit Complexity
We give new proofs of soundness (all representable functions on base types
lies in certain complexity classes) for Elementary Affine Logic, LFPL (a
language for polytime computation close to realistic functional programming
introduced by one of us), Light Affine Logic and Soft Affine Logic. The proofs
are based on a common semantical framework which is merely instantiated in four
different ways. The framework consists of an innovative modification of
realizability which allows us to use resource-bounded computations as realisers
as opposed to including all Turing computable functions as is usually the case
in realizability constructions. For example, all realisers in the model for
LFPL are polynomially bounded computations whence soundness holds by
construction of the model. The work then lies in being able to interpret all
the required constructs in the model. While being the first entirely semantical
proof of polytime soundness for light logi cs, our proof also provides a
notable simplification of the original already semantical proof of polytime
soundness for LFPL. A new result made possible by the semantic framework is the
addition of polymorphism and a modality to LFPL thus allowing for an internal
definition of inductive datatypes.Comment: 29 page
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