Commonsense Reasoning : An Event Calculus Based Approach, 2/e（Paperback）

To endow computers with common sense is one of the major long-term goals of artificial intelligence research. One approach to this problem is to formalize commonsense reasoning using mathematical logic. Commonsense Reasoning: An Event Calculus Based Approach is a detailed, high-level reference on logic-based commonsense reasoning. It uses the event calculus, a highly powerful and usable tool for commonsense reasoning, which Erik Mueller demonstrates as the most effective tool for the broadest range of applications. He provides an up-to-date work promoting the use of the event calculus for commonsense reasoning, and bringing into one place information scattered across many books and papers. Mueller shares the knowledge gained in using the event calculus and extends the literature with detailed event calculus solutions that span many areas of the commonsense world.

The Second Edition features new chapters on commonsense reasoning using unstructured information including the Watson system, commonsense reasoning using answer set programming, and techniques for acquisition of commonsense knowledge including crowdsourcing.

Drawing upon years of practical experience and using numerous examples and illustrative applications Erik Mueller shows you the keys to mastering commonsense reasoning. You’ll be able to:

• Understand techniques for automated commonsense reasoning
• Incorporate commonsense reasoning into software solutions
• Acquire a broad understanding of the field of commonsense reasoning.
• Gain comprehensive knowledge of the human capacity for commonsense reasoning

賦予電腦常識是人工智慧研究的主要長期目標之一。解決這個問題的一種方法是使用數學邏輯來形式化常識推理。《常識推理：基於事件演算的方法》是一本關於基於邏輯的常識推理的詳細高級參考書。它使用事件演算，這是一種非常強大且易於使用的常識推理工具，Erik Mueller證明它是應用範圍最廣的最有效工具。他提供了一份最新的工作，推廣使用事件演算進行常識推理，並將分散在許多書籍和論文中的信息集中在一起。Mueller分享了使用事件演算所獲得的知識，並通過詳細的事件演算解決方案擴充了相關文獻，涵蓋了常識世界的許多領域。

第二版新增了關於使用非結構化信息進行常識推理的章節，包括Watson系統、使用答案集編程進行常識推理以及常識知識獲取技術，包括群眾外包。

Erik Mueller根據多年的實踐經驗，並使用眾多示例和應用案例，向您展示了掌握常識推理的關鍵。您將能夠：
- 理解自動常識推理的技術
- 將常識推理納入軟體解決方案中
- 獲得對常識推理領域的廣泛了解
- 獲得對人類常識推理能力的全面知識