Edited: in August 2018
MORL - the Mother of All readling lists...
covering Agents, Agency and Collective Intelligence
with sincere thanks to a wise mentor, whose generosity is rivaled only by the richness of his library
Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations (*)
Multiagent systems combine multiple autonomous entities, each having diverging interests or different information. This overview of the field offers a computer science perspective, but also draws on ideas from game theory, economics, operations research, logic, philosophy and linguistics. It will serve as a reference for researchers in each of these fields, and be used as a text for advanced undergraduate or graduate courses. The authors emphasize foundations to create a broad and rigorous treatment of their subject, with thorough presentations of distributed problem solving, game theory, multiagent communication and learning, social choice, mechanism design, auctions, cooperative game theory, and modal logics of knowledge and belief. For each topic, basic concepts are introduced, examples are given, proofs of key results are offered, and algorithmic considerations are examined. An appendix covers background material in probability theory, classical logic, Markov decision processes and mathematical programming.
Understanding Agent Systems (Springer Series on Agent Technology)
...a formal approach to dealing with agents and agent systems in this second edition of Understanding Agent Systems. The Z specification language is used to establish an accessible and unified formal account of agent systems and inter-agent relationships. In particular, the framework provides precise and unambiguous meanings for common concepts and terms for agent systems, allows for the description of alternative agent models and architectures, and serves as a foundation for subsequent development of increasingly refined agent concepts
An agent-based architecture for intelligent decision support system
The Multi-agents computing paradigm offers support for large scale, widely distributed, high-performance computational systems. Several of such architectures and frameworks have been developed aimed at primarily computations in support of scientific, engineering calculations and managements. On the other hand agent software provides a number of issues including; autonomous, integrity, flexibility, ease of use and playing a number of different roles within a web scripting languages as an essential component of interactive web content to bridge the gap in these technologies. In this paper we address the architecture that support the publishing, description, managing, and communication between the agents of the business environment based on the feature that exists in the multi-agents and the agents' behaviours. This research based on multi agents approach and its associated agent description languages are used to facilitate the construction and management of ad-hoc federated software services.
Developing Intelligent Agent Systems: A Practical Guide
Intelligent agent technology is a tool of modern computerscience that can be used to engineer complex computer programmesthat behave rationally in dynamic and changing environments.Applications range from small programmes that intelligently searchthe Web buying and selling goods via electronic commerce, toautonomous space probes. This powerful technology is not widely used, however, asdeveloping intelligent agent software requires high levels oftraining and skill. The authors of this book have developedand tested a methodology and tools for developing intelligent agentsystems. With this methodology (Prometheus) developerscan start agent-oriented designs and implementations easily fromscratch saving valuable time and resources. Developing Intelligent Agent Systems not only answers thequestions “what are agents?” and “why are theyuseful?” but also the crucial question: “how do Idesign and build intelligent agent systems?” The book coverseverything a practitioner needs to know to begin to effectively usethis technology - including an introduction to the notion ofagents, a description of the concepts involved, and a softwareengineering methodology.
- a practical step-by-step introduction to designing and buildingintelligent agent systems.
- a full life-cycle methodology for developing intelligent agent systems covering specification, analysis, design and implementation of agents.
- PDT: Prometheus Design Tool – software support for the Prometheus design process.
- the example of an electronic bookstore to illustrate the design process throughout the book.
Electronic resources including the Prometheus Design Tool (PDT), can be found at:
Multiagent Systems (Intelligent Robotics and Autonomous Agents series)
Multiagent systems are made up of multiple interacting intelligent agents -- computational entities to some degree autonomous and able to cooperate, compete, communicate, act flexibly, and exercise control over their behavior within the frame of their objectives. They are the enabling technology for a wide range of advanced applications relying on distributed and parallel processing of data, information, and knowledge relevant in domains ranging from industrial manufacturing to e-commerce to health care. This book offers a state-of-the-art introduction to multiagent systems, covering the field in both breadth and depth, and treating both theory and practice. It is suitable for classroom use or independent study. This second edition has been completely revised, capturing the tremendous developments in multiagent systems since the first edition appeared in 1999. Sixteen of the book's seventeen chapters were written for this edition; all chapters are by leaders in the field, with each author contributing to the broad base of knowledge and experience on which the book rests. The book covers basic concepts of computational agency from the perspective of both individual agents and agent organizations; communication among agents; coordination among agents; distributed cognition; development and engineering of multiagent systems; and background knowledge in logics and game theory.
Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence
Multiagent systems are made up of multiple interacting intelligent agents -- computational entities to some degree autonomous and able to cooperate, compete, communicate, act flexibly, and exercise control over their behavior within the frame of their objectives. They are the enabling technology for a wide range of advanced applications relying on distributed and parallel processing of data, information, and knowledge relevant in domains ranging from industrial manufacturing to e-commerce to health care. ... introduction to multiagent systems, covering the field in both breadth and depth, and treating both theory and practice.... concepts of computational agency from the perspective of both individual agents and agent organizations; communication among agents; coordination among agents; distributed cognition; development and engineering of multiagent systems; and background knowledge in logics and game theory.
Emergence: The Connected Lives of Ants, Brains, Cities, and Software
Explaining why the whole is sometimes smarter than the sum of its parts, Johnson presents surprising examples of feedback, self-organization, and adaptive learning. How does a lively neighborhood evolve out of a disconnected group of shopkeepers, bartenders, and real estate developers? How does a media event take on a life of its own? How will new software programs create an intelligent World Wide Web?
In the coming years, the power of self-organization -- coupled with the connective technology of the Internet -- will usher in a revolution every bit as significant as the introduction of electricity. Provocative and engaging, Emergence puts you on the front lines of this exciting upheaval in science and thought.
Swarm Intelligence: From Natural to Artificial Systems (Sciences of Complexity)
Social insects--ants, bees, termites, and wasps--can be viewed as powerful problem-solving systems with sophisticated collective intelligence. Composed of simple interacting agents, this intelligence lies in the networks of interactions among individuals and between individuals and the environment. A fascinating subject, social insects are also a powerful metaphor for artificial intelligence, and the problems they solve--finding food, dividing labor among nestmates, building nests, responding to external challenges--have important counterparts in engineering and computer science. ... models of social insect behavior and how to apply these models in the design of complex systems. ... how these models replace an emphasis on control, preprogramming, and centralization with designs featuring autonomy, emergence, and distributed functioning. These designs are proving immensely flexible and robust, able to adapt quickly to changing environments and to continue functioning even when individual elements fail. In particular, these designs are an exciting approach to the tremendous growth of complexity in software and information. Swarm Intelligence draws on up-to-date research from biology, neuroscience, artificial intelligence, robotics, operations research, and computer graphics, and each chapter is organized around a particular biological example, which is then used to develop an algorithm, a multiagent system, or a group of robots.
Swarm Intelligence (The Morgan Kaufmann Series in Evolutionary Computation)
Traditional methods for creating intelligent computational systems have privileged private "internal" cognitive and computational processes. In contrast, Swarm Intelligence argues that human intelligence derives from the interactions of individuals in a social world and further, that this model of intelligence can be effectively applied to artificially intelligent systems. The authors first present the foundations of this new approach through an extensive review of the critical literature in social psychology, cognitive science, and evolutionary computation. They then show in detail how these theories and models apply to a new computational intelligence methodology―particle swarms―which focuses on adaptation as the key behavior of intelligent systems. Drilling down still further, the authors describe the practical benefits of applying particle
swarm optimization to a range of engineering problems. Developed by the authors, this algorithm is an extension of cellular automata and provides a powerful optimization, learning, and problem solving method.
.. exploring the boundaries shared by cognitive science, social psychology, artificial life, artificial intelligence, and evolutionary computation and by applying these insights to the solving of difficult engineering problems.
* Places particle swarms within the larger context of intelligent adaptive behavior and evolutionary computation.
* Describes recent results of experiments with the particle swarm optimization (PSO) algorithm
* Includes a basic overview of statistics to ensure readers can properly analyze the results of their own experiments using the algorithm.
* Support software which can be downloaded from the publishers website, includes a Java PSO applet, C and Visual Basic source code.
Superminds: The Surprising Power of People and Computers Thinking Together
If you're like most people, you probably believe that humans are the most intelligent animals on our planet. But there's another kind of entity that can be far smarter: groups of people. In this groundbreaking book, Thomas Malone, the founding director of the MIT Center for Collective Intelligence, shows how groups of people working together in superminds -- like hierarchies, markets, democracies, and communities -- have been responsible for almost all human achievements in business, government, science, and beyond. And these collectively intelligent human groups are about to get much smarter.
Using dozens of striking examples and case studies, Malone shows how computers can help create more intelligent superminds simply by connecting humans to one another in a variety of rich, new ways. And although it will probably happen more gradually than many people expect, artificially intelligent computers will amplify the power of these superminds by doing increasingly complex kinds of thinking. Together, these changes will have far-reaching implications for everything from the way we buy groceries and plan business strategies to how we respond to climate change, and even for democracy itself. By understanding how these collectively intelligent groups work, we can learn how to harness their genius to achieve our human goals.