Commonsense Reasoning (Hardcover)

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Key Phrases: trigger axioms, classical logic event calculus, discrete event calculus, Discrete Event Calculus Reasoner, Research Problem, Fluents Using (more...)

Editorial Reviews

Review

"A comprehensive exposition of reasoning about actions and change using the circumscription-based Event Calculus. The book has an excellent up-to-date bibliography on actions and change."
-Chitta Baral, Arizona State University

"Central to the idea of Artificial Intelligence is getting computers to understand simple facts about people and everyday life-what we call Common Sense. Amid the technical discussions about inference algorithms and knowledge representation, a larger question arises: What have we actually learned in the past 30 years about how to put Commonsense knowledge in computers? Look no further than Erik Mueller's Commonsense Reasoning for a deep and insightful survey of the state of the art in this topic. Some say that Commonsense defies logic; here Mueller shows that logic, at least, can put up a good fight."
-Henry Lieberman, MIT Media Laboratory

"Erik Mueller has given the most thorough treatment of common sense knowledge and reasoning yet to appear."
-John McCarthy, Stanford University

"The strength of this book is that it uses a uniform representation formalism, the event calculus, to solve a variety of commonsense reasoning problems. Researchers will find the book an inspiring tool which provides many ideas for applications of action formalisms. Thanks to both the exemplary presentation style and numerous examples, the book is also well-suited for teachers and students alike."
-Michael Thielscher, Dresden University of Technology

"Developing systems that can perform actions and deal with change is a major challenge in intelligent system design, because it requires the construction of sophisticated models for knowledge representation and reasoning. This book provides important ideas and methods which can be used to model commonsense reasoning about events in complex and dynamic environments. The content is well thought out, and difficult topics are presented in highly accessible ways. The author tells a compelling story that highlights the utility of event calculus for applications that require commonsense models of action and change."
-Mary-Anne Williams, University of Technology, Sydney, and Knowledge Representation and Reasoning Inc.

People with better commonsense than others are better observers of context and have more patterns that are more readily accessible.
Nevertheless, commonsense reasoning is an important area of study. Mueller's book will be valuable to those involved in this field.- Robert W. Ferguson, Software Quality Professional 12/06-2/07

Book Description

The only up-to-date book on logic-based commonsense reasoning.

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Product Details

• Hardcover: 432 pages
• Publisher: Morgan Kaufmann; 1 edition (February 2, 2006)
• Language: English
• ISBN-10: 0123693888
• ISBN-13: 978-0123693884
• Product Dimensions: 9.2 x 7.6 x 1.3 inches
• Shipping Weight: 2.3 pounds (View shipping rates and policies)
• Average Customer Review: 5.0 out of 5 stars  See all reviews (1 customer review)
• Amazon.com Sales Rank: #1,040,777 in Books (See Bestsellers in Books)

Customer Reviews

Most Helpful Customer Reviews

11 of 12 people found the following review helpful:

5.0 out of 5 stars A clear overview of the subject, July 30, 2006

By	Dr. Lee D. Carlson (Baltimore, Maryland USA) - See all my reviews (TOP 100 REVIEWER)    (REAL NAME)

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Occupying the time of many researchers over four decades, the goal of developing a machine that can reason in many different domains is finally reaching fruition. Progress in machine intelligence up until the last few years has been limited to abilities in a single domain, such as chess, checkers, backgammon, medical diagnostics, network management, and so on. Many researchers have held that the only way to eliminate this domain-specificity is to enable commonsense reasoning in machines. Humans of course can think in many domains. A chess master for example can also be a good writer or a good network engineer, and this is the case since any common elements in chess, writing, or network engineering can be recognized and exploited by humans. The integration and automation of commonsense reasoning in machines is challenging, but in this book an approach is outlined that has shown promise. The book of course is targeted to specialists and students in artificial intelligence, but it could also be accessible to cognitive psychologists, linguists, mathematicians, and others who are interested in the subject matter. The book is not only a theoretical discussion, for it discusses and points to practical tools that can be downloaded and used by the reader to illustrate the main issues in the book.

As the author defines it in the first paragraph of the book, commonsense reasoning as a process that takes information about a particular scenario and then makes inferences about other aspects of this scenario based on general knowledge of how the world operates. He discusses the main issues that arise in commonsense reasoning, such as the need for representing commonsense knowledge, the ability to reason about events, some of which may be concurrent or nondeterministic, and how to deal with space. Of particular importance in this discussion is the `commonsense law of inertia', which essentially makes the "intuitive" point that things will say the same unless they are affected by an event. However, this law is "violated" in many cases, the author discussing a few of these, and so a system for commonsense reasoning must be able to `release' certain `fluents' from this law.

Central to the book is the construction of the `event calculus', which is a system for representing commonsense knowledge and for implementing three types of reasoning abilities, namely `temporal projection', `abduction', and `postdiction.' The fundamental notion of course is the `event', which is an action taking place in the world. Also fundamental is the notion of a `fluent' that represents a property in the world that varies with time. All knowledge is represented declaratively in the event calculus, in order that it can be implemented in the logic programming paradigm, and it is based on a `many-sorted' extension of first-order predicate logic. Also central to the event calculus is the `timepoint' which represents an instant in time. The `discrete event calculus' is a version of the event calculus where the timepoint is restricted to the integers. Both of these systems are axiomatized early on in the book. Of particular interest and very important to commonsense reasoning is the notion of nonmonotonic reasoning and the accompanying notion of circumscription. That commonsense reasoning must be at times nonmonotonic is obvious, since certain premises held at one time may have to be altered when new information presents itself at a later time.

The event calculus is a particular formalization of commonsense reasoning, and for this to work over more than one domain it is necessary to describe formally the notion of a domain. The author calls this a `domain description' and he endeavors to make it as flexible or "elaboration tolerant" throughout the book in order that the event calculus is able to handle novel situations as they arise.

The extensive discussions and characterization of the event calculus throughout the book, as well as the examples and extensive references that are given, give the reader a solid understanding of it. Many of the concepts in the event calculus are similar to ones that are found in the other systems of artificial thought. One of these is the `triggering' of events, which is used in discrete event simulation for example, and where an event occurs if a particular condition becomes true. Events whose occurrence depends on something happening are of course very common in the real world, and any effective implementation of commonsense reasoning will have to deal with them. The challenge is to design a system that does not require all the pre-conditions be put in by hand. The axioms for triggering, along with the reasoning patterns that are used by the machine (prediction, abduction, and postdiction), should be sufficient for dealing with events that are contingent on other actions taking place. If they had to be anticipated individually, the number of statements to this effect would proliferate beyond measure, making the commonsense reasoning system extremely brittle and useless. In addition, and the author discusses this in some detail, repeated triggering must be suppressed. This is accomplished by incorporating additional trigger and effect axioms in the system.

The most interesting issue discussed in the book concerns the implementation of the mental states of `agents' in the system of commonsense reasoning. It is in this discussion that the author first introduces the concept of an agent, which he defines as an entity that engages in purposeful actions in the world. An agent can have beliefs, which can be true or false; goals, which the agent wants to be true; and plans, which are a collection of actions that the agent performs in order to reach a goal. The author formalizes these notions he gives examples. But it is when he discusses emotions that things get very complicated, for he introduces 78 axioms that he believes are needed for implementing the Ortony-Clore-Collins emotion theory. He does not discuss whether or not these axioms are independent, and from a simplicity standpoint the implementation would be more believable if the number of axioms were a lot less than the ones that are required in the book.