Generation-free Agent-based Evolutionary Computing

AbstractMetaheuristics resulting from the hybridization of multi-agent systems with evolutionary computing are efficient in many optimization problems. Evolutionary multi-agent systems (EMAS) are more similar to biological evolution than classical evolutionary algorithms. However, technological limitations prevented the use of fully asynchronous agents in previous EMAS implementations. In this paper we present a new algorithm for agent-based evolutionary computations. The individuals are represented as fully autonomous and asynchronous agents. Evolutionary operations are performed continuously and no artificial generations need to be distinguished. Our results show that such asynchronous evolutionary operators and the resulting absence of explicit generations lead to significantly better results. An efficient implementation of this algorithm was possible through the use of Erlang technology, which natively supports lightweight processes and asynchronous communication

Forensic Engineering of Advanced Polymeric Materials. Part 1 –Degradation Studies of Polylactide Blends with Atactic Poly[(R,S)-3-hydroxybutyrate] in Paraffin

The degradation of the advanced polymeric materials: blends of polylactide with poly[(R,S)-3-hydroxybutyrate] was studied in paraffin (an ingredient used in cosmetics) and compared with the degradation of pure poly[(R,S)-3-hydroxybutyrate]. The interaction between the polymeric materials studied and the paraffin was monitored during the degradation experiments, and the effects of this interaction were reported. Gel permeation chromatography, atomic force microscopy, electrospray mass spectrometry, nuclear magnetic resonance, differential scanning calorimetry and thermal gravimetric analysis revealed that degradation of the investigated materials occurs in the presence of paraffin. In the blends, poly[(R,S)-3-hydroxybutyrate] content was found to extend the disintegration time, and for the blends with good miscibility, reduced the degradation rate in the first step of degradation

The Missing Link! A New Skeleton for Evolutionary Multi-agent Systems in Erlang

Evolutionary multi-agent systems (EMAS) play a critical role in many artificial intelligence applications that are in use today. In this paper, we present a new generic skeleton in Erlang for parallel EMAS computations. The skeleton enables us to capture a wide variety of concrete evolutionary computations that can exploit the same underlying parallel implementation. We demonstrate the use of our skeleton on two different evolutionary computing applications: (1) computing the minimum of the Rastrigin function; and (2) solving an urban traffic optimisation problem. We show that we can obtain very good speedups (up to 142.44 ×× the sequential performance) on a variety of different parallel hardware, while requiring very little parallelisation effort.Publisher PDFPeer reviewe