The Common Marmoset in Captivity and Biomedical Research is the first text dedicated exclusively to this species,filling an urgent need for an encyclopedic compilation of the existing information. Sponsored by the American College of Laboratory Animal Medicine as part of its authoritative Blue Book series, the book covers the biology,management, diseases, and clinical and research applications of this important species. The common marmoset (Callithrix jacchus) has come of age in the scientific community as a behaviorally complex, cognitively advanced,small, prolific, and easily maintained nonhuman primate with many of the advantages of larger animals, such as macaques, but without the attendant physical and zoonotic risks. Marmosets are currently being used in diverse areas of inquiry, including vision and auditory research, infectious disease, cognitive neuroscience, behavior, reproductive biology, toxicology and drug development, and aging. The marmoset genome has been sequenced and there is currently an intensive effort to apply gene editing technologies to the species. The creation of transgenic marmosets will provide researchers with a small nonhuman primate model to study a number of poorly understood disorders, like autism.

The definitive presentation of Soar, one AI's most enduring architectures, offering comprehensive descriptions of fundamental aspects and new components. In development for thirty years, Soar is a general cognitive architecture that integrates knowledge-intensive reasoning, reactive execution, hierarchical reasoning, planning, and learning from experience, with the goal of creating a general computational system that has the same cognitive abilities as humans. In contrast, most AI systems are designed to solve only one type of problem, such as playing chess, searching the Internet, or scheduling aircraft departures. Soar is both a software system for agent development and a theory of what computational structures are necessary to support human-level agents. Over the years, both software system and theory have evolved. This book offers the definitive presentation of Soar from theoretical and practical perspectives, providing comprehensive descriptions of fundamental aspects and new components. The current version of Soar features major extensions, adding reinforcement learning, semantic memory, episodic memory, mental imagery, and an appraisal-based model of emotion. This book describes details of Soar's component memories and processes and offers demonstrations of individual components, components working in combination, and real-world applications. Beyond these functional considerations, the book also proposes requirements for general cognitive architectures and explicitly evaluates how well Soar meets those requirements.