This paper describes the design and implementation of robotic agents for the RoboCup Simulation 2D category that learns using a recently proposed Heuristic Reinforcement Learning a...
Luiz A. Celiberto, Carlos H. C. Ribeiro, Anna Hele...
Abstract. Cluster ensembles are deemed to be better than single clustering algorithms for discovering complex or noisy structures in data. Various heuristics for constructing such ...
In this paper we introduce the variable fitness function which can be used to control the search direction of any search based optimisation heuristic where more than one objective ...
Stephen Remde, Peter I. Cowling, Keshav P. Dahal, ...
The bin packing problem (BPP) is a real-world problem that arises in different industrial applications related to minimization of space or time. The aim of this research is to au...
Ordering heuristics are a powerful tool in CSP search algorithms. Among the most successful ordering heuristics are heuristics which enforce a fail first strategy by using the mi...
We present GP-HH, a framework for evolving local-search 3-SAT heuristics based on GP. The aim is to obtain “disposable” heuristics which are evolved and used for a specific su...
— Hyper-heuristics or “heuristics that coordinate heuristics” are fastly becoming popular for solving combinatorial optimisation problems. These methods do not search directl...
Abstract— We present a novel algorithm for the onedimension offline bin packing problem with discrete item sizes based on the notion of matching the item-size histogram with the...
Heuristics have long been recognised as a way to tackle problems which are intractable because of their size or complexity. They have been used in software engineering for purpose...
Neville Churcher, Sarah Frater, Cong Phuoc Huynh, ...
Communication overheads are one of the fundamental challenges in a multiprocessor system. As the number of processors on a chip increases, communication overheads and the distribu...
Katherine E. Coons, Behnam Robatmili, Matthew E. T...