In recent years, the evolution of artificial neural networks or neuroevolution has brought promising results in solving difficult reinforcement learning problems. But, like standa...
Abstract. This work introduces a new evolutionary algorithm that adapts the operator probabilities (rates) while evolves the solution of the problem. Each individual encodes its ge...
We present quantitative models for the selection pressure of cellular evolutionary algorithms structured in two dimensional regular lattices. We derive models based on probabilisti...
Mario Giacobini, Enrique Alba, Andrea Tettamanzi, ...
Satisfiability testing (SAT) is a very active area of research today, with numerous real-world applications. We describe CLASS2.0, a genetic programming system for semi-automatica...
In this paper, we consider a variation of the Euclidean Steiner Tree Problem in which the space underlying the set of nodes has a specified non-uniform cost structure. This proble...
Abstract. Fitness functions based on the Ising model are suited excellently for studying the adaption capabilities of randomised search heuristics. The one-dimensional Ising model ...
Abstract. The current trend in Embedded Systems (ES) design is moving towards the integration of increasingly complex applications on a single chip. An Embedded System has to satis...
To create a realistic environment, some simulations require simulated agents with human behavior pattern. Creating such agents with realistic behavior can be a tedious and time con...