Under Legg’s and Hutter’s formal measure [1], performance in easy environments counts more toward an agent’s intelligence than does performance in difficult environments. An alternate measure of intelligence is proposed based on a hierarchy of sets of increasingly difficult environments, in a reinforcement learning framework. An agent’s intelligence is measured as the ordinal of the most diffic...

Research in artificial intelligence and law goes back approximately 40 years. It remains largely based on formal logic, including non-monotonic logic, case-based reasoning, and logic programming. However, some researchers in and practitioners of law have argued in favor of quantitative approaches (e.g. probability) to account for uncertainties in legal arguments. Other researchers have pointed ...

Abstract intelligence is a human enquiry of both natural and artificial intelligence at the reductive embodying levels of neural, cognitive, functional, and logical from the bottom up. This paper describes the taxonomy and nature of intelligence. It analyzes roles of information in the evolution of human intelligence, and the needs for logical abstraction in modeling the brain and natural intel...

Students will be more likely motivated to pursue a field of study if they encounter relevant, exciting, and interesting challenges early in their studies. The NSF CCLI project “Machine Learning Laboratory Experiences for Introducing Undergraduates to Artificial Intelligence” uses machine learning as a unifying theme to teach diverse artificial intelligence (AI) topics in the context of an intro...

Artificial intelligence is a frontier field of computer science, and achieved considerable progress in the past few decades. Being an important research branch of artificial intelligence, machine learning has been successfully applied to many fields in recent years, such as expert system, automatic reasoning, natural language processing, pattern recognition, computer vision, intelligent robots,...