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.

What would it be like to speak fluent French? Is there a single moment when the language finally clicks and you understand it? When can you speak it? How long does it take? Once you can understand and speak it, does it feel as natural as English? The author wanted to find out the answers to these questions, so he moved to Paris. As he learned to speak French fluently, he kept this record of his experiences and perceptions. Included are French words and expressions, comparisons between French and English, fine points of French, and answers to the above questions.

DAYDREAMER is a cognitive architecture that models the human stream of thought and its triggering and direction by emotions, as in human daydreaming. DAYDREAMER includes: daydreaming goals: strategies for what to think about; emotional control of thought: triggering and direction of processing by emotions; hierarchical planning: achieving a goal by breaking it down into subgoals; analogical planning (chunking): storing successful plans and adapting them to future problems; episode indexing and retrieval: mechanisms for indexing and retrieval of cases; serendipity detection and application: a mechanism for recognizing and exploiting accidental relationships among problems; and action mutation: a strategy for generating new possibilities when the system is stuck. DAYDREAMER is implemented as 12,000 lines of Lisp code.

ThoughtTreasure is a commonsense knowledge base and architecture for natural language processing. It uses multiple representations including logic, finite automata, grids, and scripts. The ThoughtTreasure architecture consists of: the text agency, containing text agents for recognizing words, phrases, and names, and mechanisms for learning new words and inflections; the syntactic component, containing a syntactic parser, base rules, and filters; the semantic component, containing a semantic parser for producing a surface-level understanding of a sentence, a natural language generator, and an anaphoric parser for resolving anaphoric entities such as pronouns; the planning agency, containing planning agents for achieving goals on behalf of simulated actors; and the understanding agency, containing understanding agents for producing a more detailed understanding of a discourse.