内容
Artificial Intelligence is the study of how to build or program computers to enable them to do what minds can do. This volume discusses the ways in which computational ideas and computer modeling can aid our understanding of human and animal minds. Major theoretical approaches are outlined, as well as some promising recent developments. Fundamental philosophical questions are discussed along with topics such as: the differences between symbolic and connectionist AI, planning and problem solving, knowledge representation, learning, expert systems, vision, natural language, creativity, and human-computer interaction. This volume is suitable for any psychologist, philosopher, or computer scientist wanting to know the current state of the art in this area of cognitive science. It offers an up-to-date account of how computational ideas and techniques are relevant to psychology. It includes discussions of “classical” (symbolic) AI, of connectionism (neural nets), of evolutionary programming, and of A-Life. It discusses a wide range of psychology from low-level vision to creativity.
作者
Artificial Intelligence is the study of how to build or program computers to enable them to do what minds can do. This volume discusses the ways in which computational ideas and computer modeling can aid our understanding of human and animal minds. Major theoretical approaches are outlined, as well as some promising recent developments. Fundamental philosophical questions are discussed along with topics such as: the differences between symbolic and connectionist AI, planning and problem solving, knowledge representation, learning, expert systems, vision, natural language, creativity, and human-computer interaction. This volume is suitable for any psychologist, philosopher, or computer scientist wanting to know the current state of the art in this area of cognitive science. It offers an up-to-date account of how computational ideas and techniques are relevant to psychology. It includes discussions of “classical” (symbolic) AI, of connectionism (neural nets), of evolutionary programming, and of A-Life. It discusses a wide range of psychology from low-level vision to creativity.
目录
Preface
1 Artificial Intelligence and Agents
2 Agent Architectures and Hierarchical Control
3 Searching for Solutions
4 Reasoning with Constraints
5 Propositions and Inference
6 Planning with Certainty
7 Supervised Machine Learning
8 Reasoning with Uncertainty
9 Planning with Uncertainty
10 Learning with Uncertainty
11 Multiagent Systems
12 Learning to Act
13 Individuals and Relations
14 Ontologies and Knowledge-Based Systems
15 Relational Planning, Learning, and Probabilistic Reasoning
16 Retrospect and Prospect
A Mathematical Preliminaries and Notation
Bibliography
Index