This biographical article is written like a résumé .(July 2021) |
Rodney Brooks | |
---|---|
Born | Rodney Allen Brooks 30 December 1954 |
Nationality | Australian |
Alma mater | Stanford University Flinders University |
Awards | IJCAI Computers and Thought Award |
Scientific career | |
Fields | Robotics |
Institutions | Stanford University MIT |
Doctoral students | Lynne Parker Maja Matarić Charles Lee Isbell Jr. Cynthia Breazeal Yoky Matsuoka Holly Yanco |
Website | http://rodneybrooks.com/ |
Rodney Allen Brooks (born 30 December 1954 [1] [2] ) is an Australian roboticist, Fellow of the Australian Academy of Science, author, and robotics entrepreneur, most known for popularizing the actionist approach to robotics. He was a Panasonic Professor of Robotics at the Massachusetts Institute of Technology and former director of the MIT Computer Science and Artificial Intelligence Laboratory. He is a founder and former Chief Technical Officer of iRobot [3] and co-Founder, Chairman and Chief Technical Officer of Rethink Robotics (formerly Heartland Robotics) and currently[ when? ] is the co-founder and Chief Technical Officer of Robust.AI (founded in 2019). [4]
Brooks received a M.A. in pure mathematics from Flinders University of South Australia. [5] In 1981, he received a PhD in Computer Science from Stanford University under the supervision of Thomas Binford. [6] He has held research positions at Carnegie Mellon University and MIT and a faculty position at Stanford University. He joined the faculty of MIT in 1984. He was Panasonic Professor of Robotics at the Massachusetts Institute of Technology. He was director of the MIT Computer Science and Artificial Intelligence Laboratory (1997–2007), previously the "Artificial Intelligence Laboratory".
In 1997, Brooks and his work were featured in the film Fast, Cheap & Out of Control . [7]
Brooks became a member of the National Academy of Engineering in 2004 for contributions to the foundations and applications of robotics, including the establishment of consumer and hazardous environment robotics industries. [8]
Instead of computation as the ultimate conceptual metaphor that helped artificial intelligence become a separate discipline in the scientific community, he proposed that action or behavior are more appropriate to be used in robotics. Critical of applying the computational metaphor, even to the fields where the action metaphor is more appropriate, he wrote in 2008 that:
Some of my colleagues have managed to recast Pluto's orbital behavior as the body itself carrying out computations on forces that apply to it. I think we are perhaps better off using Newtonian mechanics (with a little Einstein thrown in) to understand and predict the orbits of planets and others. It is so much simpler. [9]
In his 1990 paper, "Elephants Don't Play Chess", [10] Brooks argued that in order for robots to accomplish everyday tasks in an environment shared by humans, their higher cognitive abilities, including abstract thinking emulated by symbolic reasoning, need to be based on the primarily sensory-motor coupling (action) with the environment, complemented by the proprioceptive sense which is a key component in hand–eye coordination, pointing out that:
Over time there's been a realization that vision, sound-processing, and early language are maybe the keys to how our brain is organized. [7]
Brooks was an entrepreneur before leaving academia to found Rethink Robotics. He was one of ten founders of Lucid Inc., and worked with them until the company's closure in 1993.[ citation needed ] Before Lucid closed, Brooks had founded iRobot with former students Colin Angle and Helen Greiner.
He experimented with off-the-shelf components, such as Fischertechnik and Lego, and tried to make robots self-replicate by putting together clones of themselves using the components. His robots include mini-robots used in oil wells explorations without cables, the robots that searched for survivors at Ground Zero in New York, and the robots used in medicine doing robotic surgery. [7]
In the late 1980s, Brooks and his team introduced Allen, a robot using subsumption architecture. As of 2012 [update] Brooks' work focused on engineering intelligent robots to operate in unstructured environments, and understanding human intelligence through building humanoid robots.[ citation needed ]
Introduced in 2012 by Rethink Robotics, an industrial robot named Baxter was intended as the robotic analogue of the early personal computer designed to safely interact with neighbouring human workers and be programmable for the performance of simple tasks. The robot stopped if it encountered a human in the way of its robotic arm and has a prominent off switch which its human partner can push if necessary. Costs were projected to be the equivalent of a worker making $4 an hour. [11]
Artificial intelligence (AI) is the intelligence of machines or software, as opposed to the intelligence of humans or animals. It is a field of study in computer science that develops and studies intelligent machines. Such machines may be called AIs.
Subsumption architecture is a reactive robotic architecture heavily associated with behavior-based robotics which was very popular in the 1980s and 90s. The term was introduced by Rodney Brooks and colleagues in 1986. Subsumption has been widely influential in autonomous robotics and elsewhere in real-time AI.
"Computing Machinery and Intelligence" is a seminal paper written by Alan Turing on the topic of artificial intelligence. The paper, published in 1950 in Mind, was the first to introduce his concept of what is now known as the Turing test to the general public.
Computer Science and Artificial Intelligence Laboratory (CSAIL) is a research institute at the Massachusetts Institute of Technology (MIT) formed by the 2003 merger of the Laboratory for Computer Science (LCS) and the Artificial Intelligence Laboratory. Housed within the Ray and Maria Stata Center, CSAIL is the largest on-campus laboratory as measured by research scope and membership. It is part of the Schwarzman College of Computing but is also overseen by the MIT Vice President of Research.
Behavior-based robotics (BBR) or behavioral robotics is an approach in robotics that focuses on robots that are able to exhibit complex-appearing behaviors despite little internal variable state to model its immediate environment, mostly gradually correcting its actions via sensory-motor links.
Evolutionary robotics is an embodied approach to Artificial Intelligence (AI) in which robots are automatically designed using Darwinian principles of natural selection. The design of a robot, or a subsystem of a robot such as a neural controller, is optimized against a behavioral goal. Usually, designs are evaluated in simulations as fabricating thousands or millions of designs and testing them in the real world is prohibitively expensive in terms of time, money, and safety.
A physical symbol system takes physical patterns (symbols), combining them into structures (expressions) and manipulating them to produce new expressions.
In artificial intelligence, model-based reasoning refers to an inference method used in expert systems based on a model of the physical world. With this approach, the main focus of application development is developing the model. Then at run time, an "engine" combines this model knowledge with observed data to derive conclusions such as a diagnosis or a prediction.
The history of artificial intelligence (AI) began in antiquity, with myths, stories and rumors of artificial beings endowed with intelligence or consciousness by master craftsmen. The seeds of modern AI were planted by philosophers who attempted to describe the process of human thinking as the mechanical manipulation of symbols. This work culminated in the invention of the programmable digital computer in the 1940s, a machine based on the abstract essence of mathematical reasoning. This device and the ideas behind it inspired a handful of scientists to begin seriously discussing the possibility of building an electronic brain.
The philosophy of artificial intelligence is a branch of the philosophy of mind and the philosophy of computer science that explores artificial intelligence and its implications for knowledge and understanding of intelligence, ethics, consciousness, epistemology, and free will. Furthermore, the technology is concerned with the creation of artificial animals or artificial people so the discipline is of considerable interest to philosophers. These factors contributed to the emergence of the philosophy of artificial intelligence.
Hubert Dreyfus was a critic of artificial intelligence research. In a series of papers and books, including Alchemy and AI (1965), What Computers Can't Do and Mind over Machine (1986), he presented a pessimistic assessment of AI's progress and a critique of the philosophical foundations of the field. Dreyfus' objections are discussed in most introductions to the philosophy of artificial intelligence, including Russell & Norvig (2021), a standard AI textbook, and in Fearn (2007), a survey of contemporary philosophy.
Nouvelle artificial intelligence (AI) is an approach to artificial intelligence pioneered in the 1980s by Rodney Brooks, who was then part of MIT artificial intelligence laboratory. Nouvelle AI differs from classical AI by aiming to produce robots with intelligence levels similar to insects. Researchers believe that intelligence can emerge organically from simple behaviors as these intelligences interacted with the "real world," instead of using the constructed worlds which symbolic AIs typically needed to have programmed into them.
This is a timeline of artificial intelligence, sometimes alternatively called synthetic intelligence.
Moravec's paradox is the observation in artificial intelligence and robotics that, contrary to traditional assumptions, reasoning requires very little computation, but sensorimotor and perception skills require enormous computational resources. The principle was articulated by Hans Moravec, Rodney Brooks, Marvin Minsky and others in the 1980s. Moravec wrote in 1988, "it is comparatively easy to make computers exhibit adult level performance on intelligence tests or playing checkers, and difficult or impossible to give them the skills of a one-year-old when it comes to perception and mobility".
Daniela L. Rus is a roboticist and computer scientist, Director of the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL), and the Andrew and Erna Viterbi Professor in the Department of Electrical Engineering and Computer Science (EECS) at the Massachusetts Institute of Technology.
Allen was a robot introduced by Rodney Brooks and his team in the late 1980s, and was their first robot based on subsumption architecture. It had sonar distance and odometry on board, and used an offboard lisp machine to simulate subsumption architecture. It resembled a footstool on wheels.
The AI effect occurs when onlookers discount the behavior of an artificial intelligence program by arguing that it is not "real" intelligence.
In artificial intelligence research, the situated approach builds agents that are designed to behave effectively successfully in their environment. This requires designing AI "from the bottom-up" by focussing on the basic perceptual and motor skills required to survive. The situated approach gives a much lower priority to abstract reasoning or problem-solving skills.
Philip E. Agre is an American AI researcher and humanities professor, formerly a faculty member at the University of California, Los Angeles. He is known for his critiques of technology. He was successively the publisher of The Network Observer (TNO) and The Red Rock Eater News Service (RRE). TNO ran from January 1994 to July 1996. RRE, an influential mailing list he started in the mid-1990s, ran for around a decade. A mix of news, Internet policy and politics, RRE served as a model for many of today's political blogs and online newsletters.
Joshua Brett Tenenbaum is Professor of Computational Cognitive Science at the Massachusetts Institute of Technology. He is known for contributions to mathematical psychology and Bayesian cognitive science. According to the MacArthur Foundation, which named him a MacArthur Fellow in 2019, "Tenenbaum is one of the first to develop and apply probabilistic and statistical modeling to the study of human learning, reasoning, and perception, and to show how these models can explain a fundamental challenge of cognition: how our minds understand so much from so little, so quickly."