Symmetry-breaking in constraint satisfaction problems (CSPs) is a well-established area of AI research which has recently developed strong interactions with symbolic computation, i...
In this paper, we present simple and genetic forms of an evolutionary paradigm known as a society of hill-climbers (SoHC). We compare these simple and genetic SoHCs on a test suite...
Gerry V. Dozier, Hurley Cunningham, Winard Britt, ...
Reinforcement learning (RL) methods have become popular in recent years because of their ability to solve complex tasks with minimal feedback. Both genetic algorithms (GAs) and te...
Abstract. In this paper, we show that the optimization of density forecasting models for regression in machine learning can be formulated as a multi-objective problem. We describe ...
The Quantified Constraint Satisfaction Problem (QCSP) has been introduced to express situations in which we are not able to control the value of some of the variables (the universa...