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Reasoning About Actions and Plans discusses approaches to a number of the more challenging problems in reasoning about the future and forming plans of action to achieve their goals. Reasoning about actions and plans can be seen as fundamental to the development of intelligent machines that are capable of dealing effectively with real-world problems. This book comprises 17 chapters, with the first delving into the semantics of STRIPS. The following chapters then discuss a theory of plans; formulating multiagent, dynamic-world problems in the classical planning framework; and a representation of parallel activity based on events, structure, and causality. Other chapters cover branching regular expressions and multi-agent plans; a representation of action and belief for automatic planning systems; possible worlds planning; and intractability and time-dependent planning. The remaining chapters discuss goal structure, holding periods and "clouds"; a model of plan inference that distinguishes between the beliefs of actors and observers; persistence, intention, and commitment; the context-sensitivity of belief and desire; the doxastic theory of intention; an architecture for intelligent reactive systems; and abstract reasoning as emergent from concrete activity. This book will be of interest to practitioners in the fields of cognition and artificial intelligence.
This book presents four contributions to planning research within an integrated framework. James Allen offers a survey of his research in the field of temporal reasoning, and then describes a planning system formalized and implemented directly as an inference process in the temporal logic. Starting from the same logic, Henry Kautz develops the first formal specification of the plan recognition process and develops a powerful family of algorithms for plan recognition in complex situations. Richard Pelavin then extends the temporal logic with model operators that allow the representation to support reasoning about complex planning situations involving simultaneous interacting actions, and interaction with external events. Finally, Josh Tenenberg introduces two different formalisms of abstraction in planning systems and explores the properties of these abstraction techniques in depth.
This work aims to construct a theory of rational decision making for real, resource-bounded, agents. Such decision making must be based on objective probabilities rather than subjective probabilities, and can't be done by choosing single action with maxmimal expected values.
This book presents four contributions to planning research within an integrated framework. James Allen offers a survey of his research in the field of temporal reasoning, and then describes a planning system formalized and implemented directly as an inference process in the temporal logic. Starting from the same logic, Henry Kautz develops the first formal specification of the plan recognition process and develops a powerful family of algorithms for plan recognition in complex situations. Richard Pelavin then extends the temporal logic with model operators that allow the representation to support reasoning about complex planning situations involving simultaneous interacting actions, and interaction with external events. Finally, Josh Tenenberg introduces two different formalisms of abstraction in planning systems and explores the properties of these abstraction techniques in depth.
Perspectives in Artificial Intelligence, Volume 1: Case-Based Planning: Viewing Planning as a Memory Task focuses on the processes, methodologies, and techniques employed in viewing planning as a memory task. The publication first elaborates on planning and memory and learning from planning. Discussions focus on learning from cases, learning plans, learning to predict failures, case-based planning, structure of case-based planning, and learning from planning. The text then elaborates on planning from memory and planning Thematic Organization Packets (TOPs) and strategies, including TOPs in understanding and planning, TOPs and strategies, and function of memory. The manuscript takes a look at modifying and repairing plans, case-based planning, and planning and planners. Topics include CHEF as a program, case-based planning as planning and learning, noticing and explaining the failure, storing the plan, different situations for altering plans, and introduction of failure. The publication is a vital reference for researchers interested in viewing planning as a memory task.
An ideal text for researchers and professionals alike, this book constitutes the refereed proceedings of the 5th International Symposium on Foundations of Information and Knowledge Systems, FoIKS 2008 held in Pisa, Italy, in February 2008. The 13 revised full papers are presented together with nine revised short papers and three invited lectures. All of these were carefully selected during two rounds of reviewing and improvement from a total of 79 submissions.
Bratman develops a planning theory of intention in this book.