This book explores the subject of artificial psychology and how the field must adapt human neuro-psychological testing techniques to provide adequate cognitive testing of advanced artificial intelligence systems. It shows how classical testing methods will reveal nothing about the cognitive nature of the systems and whether they are learning, reasoning, and evolving correctly; for these systems, the authors outline how testing techniques similar to/adapted from human psychological testing must be adopted, particularly in understanding how the system reacts to failure or relearning something it has learned incorrectly or inferred incorrectly. The authors provide insights into future architectures/capabilities that artificial cognitive systems will possess and how we can evaluate how well they are functioning. It discusses at length the notion of human/AI communication and collaboration and explores such topics as knowledge development, knowledge modeling and ambiguity management, artificial cognition and self-evolution of learning, artificial brain components and cognitive architecture, and artificial psychological modeling. Explores the concepts of Artificial Psychology and Artificial Neuroscience as applied to advanced artificially cognitive systems; Provides insight into the world of cognitive architectures and biologically-based computing designs which will mimic human brain functionality in artificial intelligent systems of the future; Provides description and design of artificial psychological modeling to provide insight into how advanced artificial intelligent systems are learning and evolving; Explores artificial reasoning and inference architectures and the types of modeling and testing that will be required to "trust" an autonomous artificial intelligent systems.
This book examines the paradigm of the engineering design process. The author discusses agile systems and engineering design. The book captures the entire design process (function bases), context, and requirements to affect real reuse. It provides a methodology for an engineering design process foundation for modern and future systems design. Captures design patterns with context for actual Systems Engineering Design Reuse and contains a new paradigm in Design Knowledge Management.
The goal of this book is to establish the foundation, principles, theory, and concepts that are the backbone of real, autonomous Artificial Intelligence. Presented here are some basic human intelligence concepts framed for Artificial Intelligence systems. These include concepts like Metacognition and Metamemory, along with architectural constructs for Artificial Intelligence versions of human brain functions like the prefrontal cortex. Also presented are possible hardware and software architectures that lend themselves to learning, reasoning, and self-evolution
Management and enables them to deal with the demands and complexities of modern, agile systems/software/hardware development teams. The book examines the project/program manager beyond the concepts of leadership and aims to connect to employees' sense of identity. The text examines human psychological concepts such as “locus of control,” which will help the manager understand their team members’ view and how best to manage their “world” contributions. The authors cover new management tools and philosophies for agile systems/software/hardware development teams, with a specific focus on how this relates to engineering and computer science. This book also includes practical case studies. Discusses management skills needed as they relate to the advances in software development practices Examines how to manage an agile development team that includes teams across geographically, ethnically, and culturally diverse backgrounds Embraces all of the aspects of modern management and leadership
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