Reinforcement Learning

Brains rule the world, and brain-like computation is increasingly used in computers and electronic devices. Brain-like computation is about processing and interpreting data or directly putting forward and performing actions. Learning is a very important aspect. This book is on reinforcement learning which involves performing actions to achieve a goal. The first 11 chapters of this book describe and extend the scope of reinforcement learning. The remaining 11 chapters show that there is already wide usage in numerous fields. Reinforcement learning can tackle control tasks that are too complex for traditional, hand-designed, non-learning controllers. As learning computers can deal with technical complexities, the tasks of human operators remain to specify goals on increasingly higher levels. This book shows that reinforcement learning is a very dynamic area in terms of theory and applications and it shall stimulate and encourage new research in this field

Advances in Reinforcement Learning

Reinforcement Learning (RL) is a very dynamic area in terms of theory and application. This book brings together many different aspects of the current research on several fields associated to RL which has been growing rapidly, producing a wide variety of learning algorithms for different applications. Based on 24 Chapters, it covers a very broad variety of topics in RL and their application in autonomous systems. A set of chapters in this book provide a general overview of RL while other chapters focus mostly on the applications of RL paradigms: Game Theory, Multi-Agent Theory, Robotic, Networking Technologies, Vehicular Navigation, Medicine and Industrial Logistic

Not for political domination: China's foreign economic policy towards Vietnam, Singapore and Malaysia in the open era

This thesis is an exploration of China’s bilateral foreign economic policy (FEP) towards Vietnam, Singapore, and Malaysia in the open era. It expects to answer the central question that what motivated China’s bilateral economic cooperation with small partners? Is it for political domination, or is it for national prosperity? Drawing upon the evidence from primary materials, this thesis challenges the hypothesis that China, as a rising economic power, intends to generate political gains from the creation of trade asymmetry of small partners. In contrast, this thesis argues that China’s bilateral economic cooperation with individual ASEAN members is for the pursuit of prosperity; in this process, the shared concerns of Beijing’s management of bilateral economic relations with individual ASEAN members are to raise the national income and to sharpen the national competitiveness in exports. In other words, Beijing’s FEP at bilateral level has the very strong implication for national economic development in general. Contrary to the realist expectations about foreign trade, this thesis shows that China did not take initiatives in bilateral economic cooperation to ensure the advantageous political gains; in addition, this thesis also finds that different political relations did not seem to affect the implementation of China’s bilateral FEP towards individual partners. By revealing China’s preference order of foreign economic cooperation at different levels, this thesis also argues that the calculations of welfare effects, rather than the consideration of relative gains, is more likely to be the determinant of China’s foreign economic behaviors

Fourth Annual Workshop on Space Operations Applications and Research (SOAR 90)

The papers from the symposium are presented. Emphasis is placed on human factors engineering and space environment interactions. The technical areas covered in the human factors section include: satellite monitoring and control, man-computer interfaces, expert systems, AI/robotics interfaces, crew system dynamics, and display devices. The space environment interactions section presents the following topics: space plasma interaction, spacecraft contamination, space debris, and atomic oxygen interaction with materials. Some of the above topics are discussed in relation to the space station and space shuttle

The 1992 Goddard Conference on Space Applications of Artificial Intelligence

The purpose of this conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The papers fall into the following areas: planning and scheduling, control, fault monitoring/diagnosis and recovery, information management, tools, neural networks, and miscellaneous applications

14th Annual Conference on Legal Issues For Financial Institutions

Materials from the 14th Annual Conference on Legal Issues For Financial Institutions held by UK/CLE in March 1994

Annual reports town officers Freedom, New Hampshire for the fiscal year ending December 31, 1977, vital statistics for 1977.

This is an annual report containing vital statistics for a town/city in the state of New Hampshire

Annual reports town officers Freedom, New Hampshire for the fiscal year ending December 31, 1977, vital statistics for 1977.

This is an annual report containing vital statistics for a town/city in the state of New Hampshire

The 1993 Goddard Conference on Space Applications of Artificial Intelligence

This publication comprises the papers presented at the 1993 Goddard Conference on Space Applications of Artificial Intelligence held at the NASA/Goddard Space Flight Center, Greenbelt, MD on May 10-13, 1993. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed

A Framework for Coordinated Control of Multi-Agent Systems

Multi-agent systems represent a group of agents that cooperate to solve common tasks in a dynamic environment. Multi-agent control systems have been widely studied in the past few years. The control of multi-agent systems relates to synthesizing control schemes for systems which are inherently distributed and composed of multiple interacting entities. Because of the wide applications of multi-agent theories in large and complex control systems, it is necessary to develop a framework to simplify the process of developing control schemes for multi-agent systems. In this study, a framework is proposed for the distributed control and coordination of multi-agent systems. In the proposed framework, the control of multi-agent systems is regarded as achieving decentralized control and coordination of agents. Each agent is modeled as a Coordinated Hybrid Agent (CHA) which is composed of an intelligent coordination layer and a hybrid control layer. The intelligent coordination layer takes the coordination input, plant input and workspace input. After processing the coordination primitives, the intelligent coordination layer outputs the desired action to the hybrid layer. In the proposed framework, we describe the coordination mechanism in a domain-independent way, as simple abstract primitives in a coordination rule base for certain dependency relationships between the activities of different agents. The intelligent coordination layer deals with the planning, coordination, decision-making and computation of the agent. The hybrid control layer of the proposed framework takes the output of the intelligent coordination layer and generates discrete and continuous control signals to control the overall process. In order to verify the feasibility of the proposed framework, experiments for both heterogeneous and homogeneous Multi-Agent Systems (MASs) are implemented. In addition, the stability of systems modeled using the proposed framework is also analyzed. The conditions for asymptotic stability and exponential stability of a CHA system are given. In order to optimize a Multi-Agent System (MAS), a hybrid approach is proposed to address the optimization problem for a MAS modeled using the CHA framework. Both the event-driven dynamics and time-driven dynamics are included for the formulation of the optimization problem. A generic formula is given for the optimization of the framework. A direct identification algorithm is also discussed to solve the optimization problem