Description:
In this chapter we study the turnpike property for the nonconvex optimal control problems described by the differential inclusion . We study the infinite horizon problem of maximizing the functional as T grows to infinity. The purpose of this chapter is to avoid the convexity conditions usually assumed in turnpike theory. A turnpike theorem is proved in which the main conditions are imposed on the mapping a and the function u. It is shown that these conditions may hold for mappings a with nonconvex images and for nonconcave functions u.
Description:
Science can be basic (or pure) and curiosity driven, or applied, in which new products or processes are developed or creative solutions to problems are sought. On the other hand, business primarily focuses on profit generation and growth. However, business itself is represented by both the service and manufacturing sectors. The benefits of science to the latter would be through the development of new products and improvement of their processes, whereas the former could also benefit from logical scientific thinking and investigation. Because small business often focuses on survival and does not have the resources to conduct the investigations required for an early response to new developments and market forces, its competitiveness can suffer. On the other hand, scientists are engrossed in their new discoveries and are usually not as adept at promoting these where they can do the most good. This chapter is a review of some historical, interspersed with current unpublished, examples of how the commercialization gap between science and business can be closed to the benefit of each. Opportunities for small and larger enterprises are described, primarily in the manufacturing sector, but benefits of science to members of the service sector that rely upon natural resources, such as drycleaners and forensic laboratories, will also be discussed. The strategies proposed highlight the importance of networking and facilitation by a ‘champion’ for the communication of innovations in a competitive environment, and the importance of marketing skills in an age of technological transparency, revolutionary advance in science, environmental sensitivity and dwindling resources. Examples range from the utilization or production of high-tech innovations to the implementation of the simplest measures for cutting costs and using resources more efficiently in small business. How the scientific/academic community can derive maximum benefits from collaborating with business is also discussed.
Description:
Researchers have consistently suggested that entrepreneurs are significant contributors to the socio-economic growth in both developed and underdeveloped nations (Paleno and Kleiner, 2000). Entrepreneurship development has been the research focus for the past few decades; however, in spite of consistent effort in this direction, developing successful entrepreneurs is one of the greatest challenges faced by any nation. Furthermore, in the light of a highly turbulent global environment coupled with a rapid pace of technological development, the need for an effective programme for developing entrepreneurs has taken priority focus in most nations (Shane and Venkataraman, 2000). Aligning our thinking with several key researchers (Clark and Sorensen, 2002; Cope and Watts, 2000; Harris et al.,2000; Honig, 2001; Jack and Anderson, 1999; Minniti and Bygrave, 2001; Rae, 2000; Sullivan, 2000), we attempted to develop and propose a pedagogy that we believe may help entrepreneurial development through education and classroom interaction. We hope our model will be useful for educators, policy makers and start-up entrepreneurs.
Description:
Multiobjective reinforcement learning algorithms extend reinforcement learning techniques to problems with multiple conflicting objectives. This paper discusses the advantages gained from applying stochastic policies to multiobjective tasks and examines a particular form of stochastic policy known as a mixture policy. Two methods are proposed for deriving mixture policies for episodic multiobjective tasks from deterministic base policies found via scalarised reinforcement learning. It is shown that these approaches are an efficient means of identifying solutions which offer a superior match to the user’s preferences than can be achieved by methods based strictly on deterministic policies.
Description:
Multiobjective reinforcement learning algorithms extend reinforcement learning techniques to problems with multiple conflicting objectives. This paper discusses the advantages gained from applying stochastic policies to multiobjective tasks and examines a particular form of stochastic policy known as a mixture policy. Two methods are proposed for deriving mixture policies for episodic multiobjective tasks from deterministic base policies found via scalarised reinforcement learning. It is shown that these approaches are an efficient means of identifying solutions which offer a superior match to the user’s preferences than can be achieved by methods based strictly on deterministic policies.
Description:
Ballarat, in the British colony of Victoria, Australia, burst into life as an instant city in 1851, following the discovery of gold. Adventurous men and women from all over the world descended on Ballarat in the 1850s, feverishly attacking the sticky clay at Golden Point. The diggers followed the gold underground, along the course of the ancient rivers, buried by the volcanic eruptions of Mounts Warrenheip and Buninyong. On the flat, 30,000 diggers collected into small cooperatives of “mates” and desperately searched for their personal Eldorado.From the first discoveries in 1851, relations between the miners and the police sent to administer the goldfields were uneasy. The government attempted to collect a monthly license fee for the right to search for gold, but the tax conferred no rights, and licenses were inspected at the point of a bayonet. The more outspoken miners, schooled in the ways of the 1848 revolutions in Europe, led a movement to protest against the gold license. The cry of “No taxation without representation” was raised, echoing the rhetoric of the American Revolution and the Chartist movement for democratic rights in Britain. [EXTRACT]
Description:
Proteins are sequences of amino acids bound into a linear chain that adopt a specific folded three-dimensional (3D) shape. This specific folded shape enables proteins to perform specific tasks. The protein structure prediction (PSP) by ab initio or de novo approach is promising amongst various available computational methods and can help to unravel the important relationship between sequence and its corresponding structure. This article presents the ab initio protein structure prediction as a conformational search problem in low resolution model using genetic algorithm. As a review, the essence of twin removal, intelligence in coding, the development and application of domain specific heuristics garnered from the properties of the resulting model and the protein core formation concept discussed are all highly relevant in attempting to secure the best solution.
Description:
Proteins are sequences of amino acids bound into a linear chain that adopt a specific folded three-dimensional (3D) shape. This specific folded shape enables proteins to perform specific tasks. The protein structure prediction (PSP) by ab initio or de novo approach is promising amongst various available computational methods and can help to unravel the important relationship between sequence and its corresponding structure. This article presents the ab initio protein structure prediction as a conformational search problem in low resolution model using genetic algorithm. As a review, the essence of twin removal, intelligence in coding, the development and application of domain specific heuristics garnered from the properties of the resulting model and the protein core formation concept discussed are all highly relevant in attempting to secure the best solution.