General Aspects of Constructing an Autonomous Adaptive Agent

There are a great deal of approaches in artificial intelligence, some of them also coming from biology and neirophysiology. In this paper we are making a review, discussing many of them, and arranging our discussion around the autonomous agent research. We highlight three aspect in our classification: type of abstraction applied for representing agent knowledge, the implementation of hypothesis processing mechanism, allowed degree of freedom in behaviour and self-organizing. Using this classification many approaches in artificial intelligence are evaluated. Then we summarize all discussed ideas and propose a series of general principles for building an autonomous adaptive agent.

Compositional hierarchical monitoring automaton construction for LTL

In this paper we give a compositional (or inductive) construction of monitoring automata for LTL formulas. Our construction is similar in spirit to the compositional construction of Kesten and Pnueli [5]. We introduce the notion of hierarchical Büchi automata and phrase our constructions in the framework of these automata. We give detailed constructions for all the principal LTL operators including past operators, along with proofs of correctness of the constructions.

Personal preferences for end-of-life care among Taiwanese community city dwellers : an inductive approach for qualitative data

Background: As an increasing number of Taiwanese people live out the final stages of their lives with chronic and complex conditions. Care decisions at the end of life can also be complex, overwhelming and stressful for an individual, family and health professionals. Understanding individuals’ wishes for end-of-life care and factors which influence individuals' decisions is important so that the provision of quality end-of-life care for all can be promoted and ensured.

Timed Probabilistic Automaton : a bridge between Raven and Song Scope for automatic species recognition

Raven and Song Scope are two automated sound anal-ysis tools based on machine learning technique for en-vironmental monitoring. Many research works have been conducted upon them, however, no or rare explo-ration mentions about the performance and comparison between them. This paper investigates the comparisons from six aspects: theory, software interface, ease of use, detection targets, detection accuracy, and potential application. Through deep exploration one critical gap is identified that there is a lack of approach to detect both syllables and call structures, since Raven only aims to detect syllables while Song Scope targets call structures. Therefore, a Timed Probabilistic Automata (TPA) system is proposed which separates syllables first and clusters them into complex structures after.

Near knowledge : inductive learning systems in law

Induction is an interesting model of legal reasoning, since it provides a method of capturing initial states of legal principles and rules, and adjusting these principles and rules over time as the law changes. In this article I explain how Artificial Intelligence-based inductive learning algorithms work, and show how they have been used in law to model legal domains. I identify some problems with implementations undertaken in law to date, and create a taxonomy of appropriate cases to use in legal inductive inferencing systems. I suggest that inductive learning algorithms have potential in modeling law, but that the artificial intelligence implementations to date are problematic. I argue that induction should be further investigated, since it has the potential to be an extremely useful mechanism for understanding legal domains.

Deductive, inductive and analogical reasoning in legal decision support systems

In this paper we provide an overview of a number of fundamental reasoning formalisms in artificial intelligence which can and have been used in modelling legal reasoning. We describe deduction, induction and analogical reasoning formalisms, and show how they can be used separately to model legal reasoning. We argue that these formalisms can be used together to model legal reasoning more accurately, and describe a number of attempts to integrate the approaches.

A SiC-based matrix converter topology for inductive power transfer system

Typical inductive power transfer (IPT) systems employ two power conversion stages to generate a high-frequency primary current from low-frequency utility supply. This paper proposes a matrix-converter-based IPT system, which employs high-speed SiC devices to facilitate the generation of high-frequency current through a single power conversion stage. The proposed matrix converter topology transforms a three-phase low-frequency voltage system to a high-frequency single-phase voltage, which, in turn, powers a series compensated IPT system. A comprehensive mathematical model is developed and power losses are evaluated to investigate the efficiency of the proposed converter topology. Theoretical results are presented with simulations, which are performed in MATLAB/Simulink, in comparison to a conventional two-stage converter. Experimental evident of a prototype IPT system is also presented to demonstrate the applicability of the proposed concept.

Five-level current-source inverters with buck-boost and inductive-current balancing capabilities

This paper presents new five-level current-source inverters (CSIs) with voltage/current buck-boost capability, unlike existing five-level CSIs where only voltage-boost operation is supported. The proposed inverters attain self-inductive-current-balancing per switching cycle at their dc front ends without having to include additional balancing hardware or complex control manipulation. The inverters can conveniently be controlled by using the well-established phase-shifted carrier modulation scheme with only two additional linear references and a mapping logic table needed. Existing modulators can therefore be conveniently retrofitted for controlling the presented inverters. By appropriately coordinating the inverter gating signals, their implementations can be realized by using the least number of components without degrading performance. These enhanced features of the inverters have already been verified in simulation and experimentally using a scaled-down laboratory platform.

Contact with existing adipose tissue is inductive for adipogenesis in matrigel

The effect of adipose tissue on inductive adipogenesis within Matrigel (BD Biosciences) was assessed by using a murine chamber model containing a vascular pedicle. Three-chamber configurations that varied in the access to an adipose tissue source were used, including sealed- and open-chamber groups that had no access and limited access, respectively, to the surrounding adipose tissue, and a sealed-chamber group in which adipose tissue was placed as an autograft. All groups showed neovascularization, but varied in the amount of adipogenesis seen in direct relation to their access to preexisting adipose tissue: open chambers showed strong adipogenesis, whereas the sealed chambers had little or no adipose tissue; adipogenesis was restored in the autograft chamber group that contained 2- to 5-mg fat autografts. These showed significantly more adipogenesis than the sealed chambers with no autograft (p < 0.01). Autografts with 1 mg of fat were capable of producing adipogenesis but did so less consistently than the larger autografts. These findings have important implications for adipose tissue engineering strategies and for understanding de novo production of adipose tissue.