Iwo Błądek

Poznan University of Technology · Institute of Computing Science

In many applications of symbolic regression, domain knowledge constrains the space of admissible models by requiring them to have certain properties, like monotonicity, convexity, or symmetry. As only a handful of variants of genetic programming methods proposed to date can take such properties into account, we introduce a principled approach capab...

Throughout centuries philosophers have attempted to understand the disparity between the conscious experience and the material world – i.e., the problem of consciousness and the apparent mind–body dualism. Achievements in the fields of biology, neurology, and information science in the last century granted us more insight into processes that govern...

When search operators in genetic programming (GP) insert new instructions into programs, they usually draw them uniformly from the available instruction set. Prefering some instructions to others would require additional domain knowledge, which is typically unavailable. However, it has been recently demonstrated that the likelihoods of instructions...

Genetic programming is an effective technique for inductive synthesis of programs from tests, i.e. training examples of desired input-output behavior. Programs synthesized in this way are not guaranteed to generalize beyond the training set, which is unacceptable in many applications. We present Counterexample-Driven Genetic Programming (CDGP) that...

Conventional genetic programming (GP) can only guarantee that synthesized programs pass tests given by the provided input-output examples. The alternative to such test-based approach is synthesizing programs by formal specification, typically realized with exact, non-heuristic algorithms. In this paper, we build on our earlier study on Counterexamp...

Genetic programming is an effective technique for inductive synthesis of programs from training examples of desired input-output behavior (tests). Programs synthesized in this way are not guaranteed to generalize beyond the training set, which is unacceptable in many applications. We present Counterexample-Driven Genetic Programming (CDGP) that emp...

Program synthesis can be posed as a satisfiability problem and approached with generic SAT solvers. Only short programs can be however synthesized in this way. Program sketching by Solar-Lezama assumes that a human provides a partial program (sketch), and that synthesis takes place only within the uncompleted parts of that program. This allows synt...

We consider simultaneous evolutionary synthesis of multiple functions, and verify whether such approach leads to computational savings compared to conventional synthesis of functions one-by-one. We also extend the proposed synthesis model with scaffolding, a technique originally intended to facilitate evolution of recursive programs, and consisting...

In this paper we study differences between contiguous and non-contiguous parallel task schedules. Parallel tasks can be executed on more than one processor simultaneously. In the contiguous schedules, indices of the processors assigned to a task must be a sequence of consecutive numbers. In the non-contiguous schedules, processor indices may be arb...