For the jailbreak mission, I used the "spy" character, whom I obtained as the reward for "freeing" the Westminster district of propaganda. Just as an aside, the Westminster mission showed the reward as a silhouette of a man with a beret, but the spy turned out to be a middle-aged woman in a sharp blazer armed with a silencer. A fellow reviewer told me he got an older black gentleman in a suit for that same mission, which indicates that even the more specialized characters are randomized. This might be worth keeping in mind for players looking for characters they think might look or dress or move a certain type of way.

It may have been the first bit of fake news in the history of the Internet: in 1984, someone posted on Usenet that the Soviet Union was joining the network. It was a harmless April's Fools Day prank, a far cry from today's weaponized disinformation campaigns and unscrupulous fabrications designed to turn a quick profit. In 2017, misleading and maliciously false online content is so prolific that we humans have little hope of digging ourselves out of the mire. Instead, it looks increasingly likely that the machines will have to save us. One algorithm meant to shine a light in the darkness is AdVerif.ai,

This overview of the Yale Artificial Intelligence Project serves as an introduction to Scientific Datalink's microfiche publication of Yale AI Technical Reports Researchers develop new ideas and plant them in programs. The programs are cultivated, hybridized, nurtured. The weaker ideas die out. The stronger ideas are grafted onto new stock and serve as the basis of hearty new strains. At Yale, there has been a traditional summer seminar series at which graduate students present their unprepossessing theories to the vocal and critical review of their colleagues.

This article gives an overview of current research on animated pedagogical agents at the Center for Advanced Research in Technology for Education (CARTE) at the University of Southern California/Information Sciences Institute. Animated pedagogical agents, nicknamed guidebots, interact with learners to help keep learning activities on track. They combine the pedagogical expertise of intelligent tutoring systems with the interpersonal interaction capabilities of embodied conversational characters. They can support the acquisition of team skills as well as skills performed alone by individuals. At CARTE, we have been developing guidebots that help learners acquire a variety of problem-solving skills in virtual worlds, in multimedia environments, and on the web.

One day a man, who had lost much of his long-term episodic memory, consulted the professor to ask him if there was any way he could help him regain the lost memories. During the previous year, this amnestic man had suffered a stroke in his right cerebral hemisphere. Being righthanded and left-hemisphere specialized for language, he was still able to speak, to read and write: and to understand what was said to him. Besides the usual difficulty in recalling proper names, his main problem involved large gaps in his memory for events that he participated in before the stroke, although he could remember events that occurred after the stroke. For example, many years before his stroke, he had received a high award for an exceptional achievement.

This article provides a personal perspective, in three stories, on the origins of AAAI. In the first story, I explain the reasons justifying AAAI's existence. In the second story, I recount some of the controvery over the name artificial intelligence, and explain why it was chosen as the new society's moniker. In the third story, I note that AI has not suffered from the applied versus research scism that has affected other societies. Finally, in the fourth story, I mention some of the early issues of finance.

To construct a perpetual self-aware cognitive agent that can continuously operate with independence, an introspective machine must be produced. To assemble such an agent, it is necessary to perform a full integration of cognition (planning, understanding, and learning) and metacognition (control and monitoring of cognition) with intelligent behaviors. The failure to do this completely is why similar, more limited efforts have not succeeded in the past. I outline some key computational requirements of metacognition by describing a multistrategy learning system called Meta-AQUA and then discuss an integration of Meta-AQUA with a nonlinear state-space planning agent. I show how the resultant system, INTRO, can independently generate its own goals, and I relate this work to the general issue of self-awareness by machine.

The Association for the Advancement of Artificial Intelligence, in cooperation with Stanford University's Department of Computer Science, was pleased to present the 2009 Spring Symposium Series, held Monday through Wednesday, March 23-25, 2009, at Stanford University. The titles of the nine symposia were Agents That Learn from Human Teachers, Benchmarking of Qualitative Spatial and Temporal Reasoning Systems, Experimental Design for Real-World Systems, Human Behavior Modeling, Intelligent Event Processing, Intelligent Narrative Technologies II, Learning by Reading and Learning to Read, Social Semantic Web: Where Web 2.0 Meets Web 3.0, and Technosocial Predictive Analytics. The goal of the Agents That Learn from Human Teachers symposium was to investigate how we can enable software and robotics agents to learn from real-time interaction with an everyday human partner. The aim of the Benchmarking of Qualitative Spatial and Temporal Reasoning Systems symposium was to initiate the development of a problem repository in the field of qualitative spatial and temporal reasoning and identify a graded set of challenges for future midterm and long-term research. The Experimental Design symposium discussed the challenges of evaluating AI systems.

Two one-day workshops were held on October 11: Intelligent Narrative Technologies, and Artificial Intelligence in the Game Design Process. The highlights of each workshop are presented in this report. Narrative is a pervasive aspect of human culture, one of the fundamental frameworks by which people view the world and comprehend their experiences. As computers and the Internet play an ever-increasing role in social interaction, education, and entertainment, they introduce novel opportunities for sharing, creating, and understanding stories. The last several years have seen growing interest and progress in computational approaches to narrative intelligence.

The software combines a broad search of online news sources with topic-specific trained models and heuristics. Since August 2010, the program has been used to operate the AI in the News service that is part of the AAAI AITopics website. The goal for NewsFinder is to publish a small, select set of news stories that are of general interest to the AI community and to provide categorization metadata to help readers scan for stories that match their specific interests. A news story may be assigned to a single category or to multiple categories (for example, Robots and Vision). Google News is driven by readers' queries to find stories containing a set of keywords from thousands of news sources.