Multiagent Systems with Symbiotic Learning and Evolution (Masbiole) has been proposed and studied, which is a new methodology of Multiagent Systems (MAS) based on symbiosis in the ecosystem. Masbiole employs a method of symbiotic learning and evolution where agents can learn or evolve according to their symbiotic relations toward others, i.e., considering the benefits/losses of both itself and an opponent. As a result, Masbiole can escape from Nash Equilibria and obtain better performances than conventional MAS where agents consider only their own benefits. This paper focuses on the evolutionary model of Masbiole, and its characteristics are examined especially with an emphasis on the behaviors of agents obtained by symbiotic evolution. In the simulations, two ideas suitable for the effective analysis of such behaviors are introduced; "Match Type Tile-world (MTT)" and "Genetic Network Programming (GNP)". MTT is a virtual model where tile-world is improved so that agents can behave considering their symbiotic relations. GNP is a newly developed evolutionary computation which has the directed graph type gene structure and enables to analyze the decision making mechanism of agents easily. Simulation results show that Masbiole can obtain various kinds of behaviors and better performances than conventional MAS in MTT by evolution.

Elevator group supervisory control systems (EGSCSs) are designed so that the movement of several elevators in a building is controlled efficiently. The efficient control of EGSCSs using conventional control methods is very difficult due to its complexity, so it is becoming popular to introduce artificial intelligence (AI) technologies into EGSCSs in recent years. As a new approach, a graph-based evolutionary method named genetic network programming (GNP) has been applied to the EGSCSs, and its effectiveness is clarified. The GNP can introduce various a priori knowledge of the EGSCSs in its node functions easily, and can execute an efficient rule-based group supervisory control that is optimized in an evolutionary way. Meanwhile, double-deck elevator systems (DDESs) where two cages are connected in a shaft have been developed for the rising demand of more efficient transport of passengers in high-rise buildings. The DDESs have specific features due to the connection of cages and the need for comfortable riding; so its group supervisory control becomes more complex and requires more efficient group control systems than the conventional single-deck elevator systems (SDESs). In this paper, a new group supervisory control system for DDESs using GNP is proposed, and its optimization and performance evaluation are done through simulations. First, optimization of the GNP for DDSEs is executed. Second, the performance of the proposed method is evaluated by comparison with conventional methods, and the obtained control rules in GNP are studied. Finally, the reduction of space requirements compared with SDESs is confirmed.Index Terms-Double-deck elevator, elevator group supervisory control systems (EGSCS), evolutionary optimization, genetic network programming (GNP).

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This paper explores the adaptability of buildings in Japan from the perspective of three distinct practice typologies: large general contractors, large architectural design firms, and small design ateliers. The paper illustrates the cultivation of adaptability in Japan revealing a maturing of concepts into current innovations, trends, priorities, and obstacles in relation to adaptability in design. The paper contextualizes the situation by reviewing the evolution of residential development in support of building adaptability, and the ways in which these policies and concepts have shaped practice and transcended residential design. This evolution is then explored through non-residential case studies undertaken by the three practice types, and supported through a review of critical themes emerging from the interviews. The importance of particular physical characteristics are examined including storey height, location of services, planning modules and structural spacing/spans. The interviews expose the critical relationship between adaptability and different social variables - the state of the market, the role of planning regulations and other legal frameworks; as well as, the misconceptions and variations in the perceptions on the role and meaning adaptability has in practice. The paper is concluded by revealing the lessons learnt, including the unfolding of dependencies outside the ‘black box’ of adaptability (e.g. practice culture, material and, stakeholder mindsets) and the requirement of effective communication of concepts to allow an informed conversation between professionals and with clients and users. Like many other philosophical design concepts in complex processes, adaptability benefits from a mutual understanding, good relationships, communication, integration, and shared goals amongst team members.

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Porphyromonas gingivalis, Bacteroides forsythus, and Treponema denticola have been found to predominate in periodontal pockets of patients with adult periodontitis. These microorganisms hydrolyze the synthetic peptide N-benzoyl-DL-arginine-2-naphthylamide (BANA). In this study, we developed an enzymatic method, designated SK-013, to detect the existence of these microorganisms in subgingival plaque bacteria. This enzymatic method was based on the observation of the hydrolysis of N-carbobenzoxy-glycyl-glycyl-arginyl-3,5-dibromo-4-hydroxyaniline (N-CBz-Gly-Gly-Arg-DBHA) and made more sensitive by adding an enhancing system. The SK-013 was specifically positive for P. gingivalis, B. forsythus, T. denticola, and some strains of Capnocytophaga species, but was not specific for any of the other bacterial strains tested. This SK-013 system may be valuable for detection and quantification of periodontal disease-associated bacteria in subgingival plaque and thus for diagnosis of periodontal infections.

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