Rodney A. Brooks
Jump to navigation
Jump to search
Rodney A. Brooks is a person.
- See: Robotics, Rethink Robotics.
References
2018
- (Brooks, 2018a) ⇒ Rodney A. Brooks. (2018). “My Dated Predictions." Blog post
2016
- (Stone et al., 2016) ⇒ Peter Stone, Rodney A. Brooks, Erik Brynjolfsson, Ryan Calo, Oren Etzioni, Greg Hager, Julia Hirschberg, Shivaram Kalyanakrishnan, Ece Kamar, Sarit Kraus, Kevin Leyton-Brown, David Parkes, William Press, AnnaLee Saxenian, Julie Shah, Milind Tambe, and Astro Teller. (2016). “Artificial Intelligence and Life in 2030." One Hundred Year Study on Artificial Intelligence: Report of the 2015-2016 Study Panel,.” In: Stanford University Journal.
2014
- (Brooks, 2014) ⇒ Rodney A. Brooks. (2014). “Artificial intelligence is a tool, not a threat.” In: Rethinking Robotics, November 10, 2014.
2013
- http://en.wikipedia.org/wiki/Rodney_Brooks
- Rodney Allen Brooks FAA (born December 30, 1954) is an Australian computer scientist and former Panasonic Professor of Robotics at the Massachusetts Institute of Technology. Since 1986 he has authored a series of highly influential papers which have inaugurated a fundamental shift in artificial intelligence research. Outside the scientific community Brooks is also known for his appearance in a film featuring him and his work, Fast, Cheap, and Out of Control.
He is now the chairman and chief technical officer for Rethink Robotics (formerly Heartland Robotics) in Boston.
- Rodney Allen Brooks FAA (born December 30, 1954) is an Australian computer scientist and former Panasonic Professor of Robotics at the Massachusetts Institute of Technology. Since 1986 he has authored a series of highly influential papers which have inaugurated a fundamental shift in artificial intelligence research. Outside the scientific community Brooks is also known for his appearance in a film featuring him and his work, Fast, Cheap, and Out of Control.
1991
- (Brooks, 1991) ⇒ Rodney A. Brooks. (1991). “Intelligence Without Representation.” In: Artificial intelligence, 47(1).
- ABSTRACT: Artificial intelligence research has foundered on the issue of representation. When intelligence is approached in an incremental manner, with strict reliance on interfacing to the real world through perception and action, reliance on representation disappears. In this paper we outline our approach to incrementally building complete intelligent Creatures. The fundamental decomposition of the intelligent system is not into independent information processing units which must interface with each other via representations. Instead, the intelligent system is decomposed into independent and parallel activity producers which all interface directly to the world through perception and action, rather than interface to each other particularly much. The notions of central and peripheral systems evaporate — everything is both central and peripheral. Based on these principles we have built a very successful series of mobile robots which operate without supervision as Creatures in standard office environments.
1990
- (Brooks, 1990) ⇒ Rodney A. Brooks. (1990). “Elephants Don't Play Chess.” In: Robotics and autonomous systems, 6(1).
- ABSTRACT: There is an alternative route to Artificial Intelligence that diverges from the directions pursued under that banner for the last thirty some years. The traditional approach has emphasized the abstract manipulation of symbols, whose grounding in physical reality has rarely been achieved. We explore a research methodology which emphasizes ongoing physical interaction with the environment as the primary source of constraint on the design of intelligent systems. We show how this methodology has recently had significant successes on a par with the most successful classical efforts. We outline plausible future work along these lines which can lead to vastly more ambitious systems.
1989
- (Brooks, 1989) ⇒ Rodney A. Brooks. (1989). “A Robot That Walks; emergent behaviors from a carefully evolved network." Neural computation, 1(2).
- ABSTRACT: Most animals have significant behavioral expertise built in without having to explicitly learn it all from scratch. This expertise is a product of evolution of the organism; it can be viewed as a very long-term form of learning which provides a structured system within which individuals might learn more specialized skills or abilities. This paper suggests one possible mechanism for analagous robot evolution by describing a carefully designed series of networks, each one being a strict augmentation of the previous one, which control a six-legged walking machine capable of walking over rough terrain and following a person passively sensed in the infrared spectrum. As the completely decentralized networks are augmented, the robot's performance and behavior repertoire demonstrably improve. The rationale for such demonstrations is that they may provide a hint as to the requirements for automatically building massive networks to carry out complex sensory-motor tasks. The experiments with an actual robot ensure that an essence of reality is maintained and that no critical disabling problems have been ignored.