Of course, this is far from the first attempt to plot a course toward human-level AGI: arguably this was the goal of the founders of the field of artificial intelligence in the 1950s, and has been pursued by a steady stream of AI researchers since, even as the majority of the AI field has focused its attention on more narrow, specific subgoals. The ideas presented here build on the ideas of others in innumerable ways, but to review the history of AI and situate the current effort in the context of its predecessors would require a much longer article than this one. Thus we have chosen to focus on the results of our AGI roadmap discussions, acknowledging in a broad way the many debts owed to many prior researchers. References to the prior literature on evaluation of advanced AI systems are given by Laird (Laird et al. 2009) and Geortzel and Bugaj (2009), which may in a limited sense be considered prequels to this article. We begin by discussing AGI in general and adopt a pragmatic goal for measuring progress toward its attainment. An initial capability landscape for AGI The heterogeneity of general intelligence in will be presented, drawing on major themes from humans makes it practically impossible to develop developmental psychology and illuminated by a comprehensive, fine-grained measurement system mathematical, physiological, and informationprocessing for AGI. While we encourage research in defining perspectives. The challenge of identifying such high-fidelity metrics for specific capabilities, appropriate tasks and environments for measuring we feel that at this stage of AGI development AGI will be taken up. Several scenarios will a pragmatic, high-level goal is the best we can be presented as milestones outlining a roadmap agree upon. I advocate beginning with a system that has minimal, although extensive, built-in capabilities. Many variant approaches have been proposed A classic example of the narrow AI approach was for achieving such a goal, and both the AI and AGI IBM's Deep Blue system (Campbell, Hoane, and communities have been working for decades on Hsu 2002), which successfully defeated world chess the myriad subgoals that would have to be champion Gary Kasparov but could not readily achieved and integrated to deliver a comprehensive apply that skill to any other problem domain without AGI system.

Many human social exchanges and coordinated activities critically involve dialogue interactions. Hence, we need to develop natural humanlike dialogue processing mechanisms for future robots if they are to interact with humans in natural ways. In this article we discuss the challenges of designing such flexible dialogue-based robotic systems. We report results from data we collected in human interaction experiments in the context of a search task and show how we can use these results to build more flexible robotic architectures that are starting to address the challenges of task-based humanlike natural language dialogues on robots.

Many human social exchanges and coordinated activities critically involve dialogue interactions. Hence, we need to develop natural humanlike dialogue processing mechanisms for future robots if they are to interact with humans in natural ways. In this article we discuss the challenges of designing such flexible dialogue-based robotic systems. We report results from data we collected in human interaction experiments in the context of a search task and show how we can use these results to build more flexible robotic architectures that are starting to address the challenges of task-based humanlike natural language dialogues on robots.

In this paper, we address the problem of communicating, interpreting,and executing complex yet abstract instructions to a robot teammember. This requires specifying the tasks in an unambiguous manner,translating them into operational procedures, and carrying outthose procedures in a persistent yet reactive manner. We reportour response to these issues, after which we demonstrate theircombined use in controlling a mobile robot in a multi-room officesetting on tasks similar to those in search-and-rescue operations.We conclude by discussing related research and suggesting directionsfor future work.

Consider the following problem: a human-robot team is actively In this paper, we explore the issues involved in engineering engaged in an urban search and rescue (USAR) scenario an automated planner to guide a robot towards maximizing inside a building of interest. The robot is placed inside net benefit accompanied with goal achievement in such this building, at the beginning of a long corridor; a sample scenarios. The planning problem that we face involves partial layout is presented in Figure 1. The human team member satisfaction (in that the robot has to weigh the rewards of has intimate knowledge of the building's layout, but is removed the soft goals against the cost of achieving them); it also requires from the scene and can only interact with the robot replanning ability (in that the robot has to modify its via on-board wireless audio communication. The corridor in current plan based on new goals that are added). An additional which the robot is located has doors leading off from either (perhaps more severe) complication is that the planner side into rooms, a fact known to the robot. However, unknown needs to handle goals involving objects whose existence is to the robot (and the human team member) is the possibility not known in the initial state (e.g., the location of the humans that these rooms may contain injured humans (victims).

This communication is accomplished via and Scheutz in preparation). The observed naturallytimed strategies which necessarily incorporate time. The interaction interaction is used to argue that in at least some interesting between the agents is naturally extended over time, yet interactive situations, explicit representation of or in neither agent does any explicit representation of or reasoning operation on time is not necessary. Observing that many interactive about time occur. Kelso et al's Virtual Partner Interaction situations will be similar, we hypothesize that in (Kelso et al. 2009) is a paradigm in which a virtual fact most interactions will require no explicit representation hand is guided by a dynamical system known to guide most or reasoning about time.

The third international conference on Human-Robot Interaction (HRI-2008) was held in Amsterdam, The Netherland, March 12-15, 2008. The theme of HRI-2008, "Living With Robots", highlights the importance of the technical and social issues underlying human-robot interaction with companion and assistive robots for long-term use in everyday life and work activities. More than two hundred and fifty researchers, practitioners, and exhibitors attended the conference, and many more contributed to the conference as authors or reviewers. HRI-2009 will be held in San Diego, California from March 11-13, 2009.

Human-Robot Interaction (HRI-2008) with robots," highlights the importance It also featured Foundation, and the European a panel on "robo-ethics" intended Network for the Advancement of Artificial to start a discussion of the ethical Cognitive Systems (EU Cognition) and societal implications of provided grants. More than 250 autonomous robots and a panel on representatives from academia, government, "what is HRI?" that examined the constitutive and industry attended HRI-components of human-robot 2008. HRI is the premier forum for the Of the 134 submissions, the program presentation and discussion of committee accepted 48 full research results in human-robot interaction. Human-robot interaction 27 submissions) were featured in a special is inherently interdisciplinary session. The workshops artificial intelligence, cognitive science, addressed metrics (an examination of ergonomics, human-computer proposed guidelines for evaluating interaction, psychology, robotics, and HRI), coding behavioral video data other fields. From 1997 to 2000, he was vice president of development for Fourth Planet, Inc., a developer of real-time visualization software. Fong has published more than 50 papers in field robotics, human-robot interaction, virtual reality user interfaces, and parallel processing, was chair of the 2006 AAAI Spring Symposium on human-robot interaction in space, and is cogeneral chair for HRI-2008. Kerstin Dautenhahn is the research professor of artificial intelligence in the School of Computer Science and coordinator of the Adaptive Systems Research Group at the University of Hertfordshire in the United Kingdom. Save the Date! -- July 11-15, 2010 AAAI comes to Atlanta, Georgia in 2010! Please mark your calendars, and visit www. She was general chair of IEEE RO-MAN06 and cogeneral chair of HRI-2008. Scheutz was the coprogram chair for HRI-Seven student teams competed to award went to "Robots in Organizations: University of Amsterdam took top Jodi Forlizzi.

The Fifteenth Annual AAAI Robot Competition and Exhibition was held at the Twenty-First National Conference on Artificial Intelligence in Boston, Massachusetts, in July 2006. This article describes the events that were held at the conference, including the Scavenger Hunt, Human Robot Interaction, and Robot Exhibition.

The Fifteenth Annual AAAI Robot Competition and Exhibition was held at the Twenty-First National Conference on Artificial Intelligence in Boston, Massachusetts, in July 2006. This article describes the events that were held at the conference, including the Scavenger Hunt, Human Robot Interaction, and Robot Exhibition.