If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Alves-Oliveira, Patrícia (Instituto Universitário de Lisboa) | Freedman, Richard G. (University of Massachusetts Amherst) | Grollman, Dan (Sphero, Inc.) | Herlant, Laura (arnegie Mellon University) | Humphrey, Laura (Air Force Research Laboratory) | Liu, Fei (University of Central Florida) | Mead, Ross (Semio) | Stein, Frank (IBM) | Williams, Tom (Tufts University) | Wilson, Shomir (University of Cincinnati)
Amato, Christopher (University of New Hampshire) | Amir, Ofra (Harvard University) | Bryson, Joanna (University of Bath) | Grosz, Barbara (Harvard University) | Indurkhya, Bipin (Jagiellonian University) | Kiciman, Emre (Microsoft Research) | Kido, Takashi (Rikengenesis) | Lawless, W. F. (Massachusetts Institute of Technology) | Liu, Miao (University of Southern California) | McDorman, Braden (Semio) | Mead, Ross (University of Amsterdam) | Oliehoek, Frans A. (University of Pennsylvania) | Specian, Andrew (American University in Paris) | Stojanov, Georgi (University of Electro-Communications) | Takadama, Keiki
The Association for the Advancement of Artificial Intelligence, in cooperation with Stanford University's Department of Computer Science, presented the 2016 Spring Symposium Series on Monday through Wednesday, March 21-23, 2016 at Stanford University. The titles of the seven symposia were (1) AI and the Mitigation of Human Error: Anomalies, Team Metrics and Thermodynamics; (2) Challenges and Opportunities in Multiagent Learning for the Real World (3) Enabling Computing Research in Socially Intelligent Human-Robot Interaction: A Community-Driven Modular Research Platform; (4) Ethical and Moral Considerations in Non-Human Agents; (5) Intelligent Systems for Supporting Distributed Human Teamwork; (6) Observational Studies through Social Media and Other Human-Generated Content, and (7) Well-Being Computing: AI Meets Health and Happiness Science.
This work explores possible applications of electromagnetic platform stabilization (EPS) in systems suffering from vibration and resonance along multiple axes. Many HRI platforms are coupled rigid-body platforms; an EPS system acts as a non-rigid coupling between the mobile base and the upper-body structure. Electromagnets have many qualities that have been shown to perform well in complex mechanical systems; our initial investigations illustrate the utility of EPS technologies for reducing resonance in mobile robot platforms, particularly in human-robot interactions, in which sensors in the upper-body structure must be stable to track human users.
A multi-robot system, like a robot formation, contains information that is distributed throughout the system. As the collective increases in numbers or explores distant or difficult areas, obtaining collective situational awareness becomes critical. We propose a method for extracting system and environmental information distributed over a collective of robots.
Clair, Aaron St. (University of Southern California) | Atrash, Amin (University of Southern California) | Mead, Ross (University of Southern California) | Mataric, Maja (University of Southern California)
Effective communication is often required for agents to properly handle collaborative multi-agent tasks. This is particularly true when humans are working alongside synthetic agents and traditional wireless communication modes are impractical. A framework for communication must allow for both explicit communication, where actions are directly execute to convey information, and implicit communication, where the agent projects information indirectly as a consequence of actions taken to achieve the tasks. We propose a Theory of Mind-based approach to communication that allows an agent to reason about its own state, the states of the other agents, and the other agents’ beliefs about each other’s state.
The field of multi-robot coordination, specifically robot formation control, is rapidly expanding, with many applications proposed. In our previous work, we considered the problem of establishing and maintaining a formation of robots given an already connected network. We now propose a distributed auction-based method to autonomously initialize and reorganize the network structure of a formation of robots.