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The "Bionic Woman" NASA Intelligent Robots

The "Bionic Woman" NASA uses artificial intelligence to teach robots what to do to behave more like human explorers.

May 29, 2001 - Ayanna Howard may never set foot on Mars, or lead a mission to Jupiter, but the work she is doing on robots "smart" help, however to revolutionize planetary exploration.
As Project Scientist, specializing in artificial intelligence Propulsion Laboratory NASA's Jet (JPL), Ayanna is part of a group that applies creative energy to a new generation of space missions - exploring the surface of planets and the Moon for autonomous robots able to "think" for themselves themselves.
Up: You may not resemble the android Data from Star Trek, but in future robotic explorers as it possess artificial intelligence that enable them to explore the terrain without human supervision. Image courtesy of JPL.
To receive breaking science news, subscribe here Almost all robotic spacecraft used today are inflexible in how they respond to the difficulties encountered (an important exception is the Deep Space 1 that uses artificial intelligence technology.) These robots can only perform activities that are explicitly written is the software or through instructions sent via radio by a human controller on Earth.
During the exploration of unknown planets, a million miles from Earth, this variety of robot, such as "dog obedience" requires constant attention from humans. In comparison, the ultimate goal of Ayanna and her colleagues is to "put a robot on Mars and let him work alone without direct human intervention."
"We want instructing the robot to think about possible obstacles you may encounter, just as you would an astronaut in the same situation, "he says." Our job is to help the robot to think in more logical terms about turn right or left, not just a few degrees of rotation. "
How can a robot can make decisions like a human?
Scientists have developed appropriate techniques, learning ability and visual observation of humans.
The Humans do not have a rule book or a program that check for every move you make, write Ayanna - we are much more clever than that.'s work his group is designing robots that can emulate, not just the thought process and analysis of humans in determining the characteristics of the land, but also the human ability to drive a vehicle in real time.
Above: Ayanna Howard received a doctorate in electrical engineering from the University of Southern California, specializing in artificial intelligence and robotics. He has worked at JPL since 1993.

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To achieve this, Ayanna and her colleagues have two concepts in the field of artificial intelligence: "fuzzy logic" (fuzzy logic, in English) and "neural networks."
Fuzzy logic allows computers to operate not only in terms of black and white - true or false - but also in terms of shades of gray. For example, a traditional computer would take the height of a tree and assigned the category of - "high." But a computer equipped with fuzzy logic would say that the tree has a probability of 78 percent (for example) to be in the category of "high" and 22 percent belong to some other category. The exact distinction between "high" and "low" is now confused.
The power of the computer to define categories based on an approach de probabilidades le permite al computador aprender de sus experiencias, puesto que la asignación de probabilidad puede ser modificada la próxima vez que encuentre un objeto similar. La lógica confusa ya es utilizada en software para programas de computadores en reconocimiento de voz y escritura manual, los cuales aprenden a mejorar su desempeño a través de "entrenamiento."
Arriba: La combinación de lógica confusa y de redes neurales permite que los nuevos robots detecten un obstáculo en un terreno desconocido (izquierda, una secuencia de una imagen siendo procesada), juzgar la seguridad relativa de varias rutas alternas, y establecer una ruta hacia su destino (derecha, un panorama con tres imágenes), todo esto without a human guide them in real time.
Neural networks also have the ability to learn from their experiences. This should not be surprising since the neural network design duplicates the way the brain cells - called neurons - process information

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"Neural networks generalized inputs allow you to associate a specific result, "says Ayanna. "When a person sees and hears all fours barking (income), her experience allows us to conclude that this is a dog (the result)." This feature of neural networks enable a new robot select behaviors or paths to follow according to general elements of their surroundings, much like what humans do.
To do this, neural networks contain several layers of "nodes," which are analogous to neurons. Each node in a layer is connected to nodes in other layers. The signals travel in this network of connections, and each node acts as a gate, letting only signs of some magnitude. The network "learns" by adjusting the threshold for each individual node.
Above: In this simplified example of a neural network, input signals are connected to the yellow layer on the left, pass through two layers of process, and then emerge on the right as signs output. This architecture can run surprisingly sophisticated logic problems, especially when feedback loops are added.
This graph of neural networks, which can be drawn on a napkin, it may seem very simple, but in practice, these artificial brains can run incredibly complex logic problems. Ayanna neural networks called "black box technology" - in other words, what happens between the input layer and the output is so difficult to decipher which scientists treat it as a "black box" in a way or other converts inputs into outputs.
Combining these two technologies, Ayanna and her colleagues at JPL expect to create a "brain" robot which alone can learn to walk on unfamiliar terrain of other planets.

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The "Bionic Woman" NASA uses artificial intelligence to teach robots what to do to behave more like human explorers.

May 29, 2001 - Ayanna Howard may never set foot on Mars, or lead a mission to Jupiter, but the work she is doing on robots "smart" help, however, revolutionize exploration planet.
As Project Scientist, specializing in artificial intelligence at Jet Propulsion Laboratory of NASA (JPL), Ayanna is part of a group that applies creative energy to a new generation of space missions - exploring the surface of planets and the Moon for autonomous robots able to "think" for themselves.
Up: You may not resemble the android Data from Star Trek, but in future robotic explorers as it possess artificial intelligence that enable them to explore the terrain without human supervision. Image courtesy of JPL. Most vehicles
space robot used today are inflexible in how they respond to the difficulties encountered (an important exception is the Deep Space 1 employing artificial intelligence technology.) These robots can only perform activities that are explicitly written is the software or through instructions sent via radio by a human controller on Earth.
During the exploration of unknown planets, a million miles from Earth, this variety of robot, such as "dog obedience" requires constant attention from humans. In comparison, the ultimate goal of Ayanna and her colleagues is to "put a robot on Mars and let him work alone without direct human intervention. "
" We want to instruct the robot to think about possible obstacles you may encounter, just as you would an astronaut in the same situation, "he says." Our job is to help the robot to think in logical terms about turning left or right, not just a few degrees of rotation. "

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NAVEGACIÓN POR EL RÍO SINÚ

"Before the water came up there, all that you see to the edge was full of trees, look for the other side and you imagine that the forest was one"-as we sailed by the Urra dam in under the referendum on water and pre-IV Latin American Meeting of People Affected by Dams, indigenous people with their body painted and wearing beautiful necklaces of colored beads, recalled with nostalgia the Sinu river once that not only was the spiritual foundation of the people Embera Katío but also the protein source that guaranteed food for everyone.

The ride to Begidó community is a graveyard of giant trees that stood on the water, robust vegetation that took hundreds of years stand as monuments of nature and now, drowned and dead, we remember the negative impacts that development at close range causes not only the nature but also to communities. The referendum on water embarked on a new navigation the Sinu river eight years ago was dammed to make way for I Urra hydroelectric project, which not only impacted in irreversible and harmful to the rainforest but also caused severe damages the Embera people seated at the high, as well as fishing communities and farmers of the middle and lower basin. Navigation is made up of delegates from Chile, Mexico and Guatemala, along with other sailors from various social processes of Chucurí San Vicente, Buenos Aires-Suárez, Guarinocito, Manizales, Southern Territory (Tunjuelo basin) in Bogota and La Cocha in Nariño, several of whom have hydroelectric bias in their territories.

The dairy Begidó community (where he was from the leader Kimy Pernia Domico killed for opposing Urrá) turned the night into a huge tower of babel cooled by the mysterious sounds of the forest and the river Esmeralda its way into the forest. In the midst of the deep night and strangers shared experiences and knowledge, "what they want is our movement and get us out of the basin, so we shake hands to all and keep us informed, this alliance must be strengthened so to fight together, "said the indigenous governor of the Town Council and to the attendees.

that extent the task of collecting the necessary signatures for the referendum on water succeed, feeds on more and new reasons from regions country, which in its bucolic and simple language are questioning the entire Colombian nation about the real meaning of development that comes without risk impoverishing many communities to the detriment of the country's most coveted treasure: our water potential.

While the impacts of hydropower, obviously harmful, threatening a new project to come: Sinu Urra II or Project, the thrust would be fatal to these fragile ecosystems and communities developed there. Listening to the price paid in life that many leaders to lead the opposition to the work, seeing prejudices acute nature, the river, knowing now that bocachico eg sold out because their migratory spawning is interrupted by an impenetrable gray walls, knowing the contradictions of a project that was presented as the panacea for floods (the Last year Sinú overflowed flooding ever to the people of the middle and low) ... knowing, seeing, hearing and feeling we wonder why they want to build a dam whose impacts will be five or even six times higher?

Motivated by the force that gives the reason and encouraged to know that our motives are concentrated now in the referendum on water, the fluvionavegantes embarked Tierralta and back to Monteria where all our impulses would focus on collecting items for which the Colombian people to rule in favor of water and life.

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intelligent robots have three levels of consciousness


interdisciplinary knowledge embodied cognitive science and artificial intelligence can conceive new advanced systems capable of govern. The highest level of these systems is represented by the so-called three-tier architecture that includes three processes related to Freud's theory on the integration of the id, the superego and the ego. Reactant levels, deliberative and reflective are the future features of intelligent robots. By Sergio Moriello.

Agents can be defined in several ways and there is to date no universally accepted definition. In its simplest form, an agent is a complex adaptive system that can sense and act on their environment (which may be real or simulated) [Moriello, 2005, p. 137].

For Stuart Russell and Peter Norvig, an "agent" is all that can be viewed as perceiving its environment through sensors and acting upon that environment through their effectors [Russell and Norvig, 1996, p. 33]. That is, its main feature is that it is "located" (situatedness) is embedded within a local environment with which it interacts and which influences, directly, on their behavior [Florian, 2003] [Muñoz Moreno, 2000 ] [Badano Innocenti, 2000].

An "autonomous agent" is one that interacts, by itself, with its surrounding environment. For that, you should be able to perceive, reason and act. In other words, should have appropriate sensors to collect information from both of their intorno and its environment (perceived) needs to be able to turn that information into knowledge and use it to achieve its objectives (reason) and must have appropriate effectors likely to change the environment (acting) [Moriello, 2005, p. 221 / 2]. Intelligent Agents



An "autonomous intelligent agent" is one that can detect and record whether an action done in a given situation was favorable [Fritz, García Martínez and Marsiglio, 1990, p. 3] [García Martínez, 1997, p. 3]. In this way, you can gain experience and adjust their behavior as you learn.

animals perceive their environment (and its intorno) through their sensory systems; process that information (assimilating, classifying and interpreting) through the neural circuits of cerebral cortex, and acting-out, thanks to the appliance-musculoskeletal and inward-through homeostatic mechanisms. But the overall process is not unidirectional and linear, but circular and cyclical: perception interprets reality through action, body movement [Moriello, 2005, p. 233].

Finally, it should be noted that, although not necessarily, an autonomous intelligent agent "is embodied" (embodiment) has a physical body capable of experiencing its environment directly. Their actions have immediate feedback on their own perceptions [Florian, 2003] [Muñoz Moreno, 2000] [Badano Innocenti, 2000].

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An "autonomous intelligent agent" is one that can detect and record whether an action done in a given situation was favorable [Fritz, García Martínez and Marsiglio, 1990, p. 3] [García Martínez, 1997, p. 3]. In this way, you can gain experience and adjust their behavior as you learn.

animals perceive their environment (and its intorno) through its sensory systems, process that information (Assimilating, classifying and interpreting) through the neural circuits of cerebral cortex, and acting-out, thanks to its unit-musculoskeletal and inward-through homeostatic mechanisms. But the overall process is not unidirectional and linear, but circular and cyclical: perception interprets reality through action, body movement [Moriello, 2005, p. 233].

Finally, it should be noted that, although not necessarily, an autonomous intelligent agent "is embodied" (embodiment) has a physical body able to experience their environment directly. Their actions have immediate feedback on their own perceptions [Florian, 2003] [Muñoz Moreno, 2000] [Badano Innocenti, 2000].

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Intelligent Agents Regulations and Controls Intelligent Autonomous Agents




can define the concept of "governance" (translation of the English word "governance") as the way a complex system is self-government (self-guided and self-directed ) to a previously defined goal.

The main objective intrinsic (ie, the "attractor" principal) of any system is its own survival, however, there are several sub-objectives. Thus, according to American psychologist Abraham Maslow, in humans there is a hierarchy of objectives that seek to satisfy: physiological, security, belonging, esteem and personal fulfillment.

An autonomous agent has different regulatory mechanisms that allow you to maintain dynamic equilibrium. These mechanisms consist, in turn, by different feedback loops (both negative and positive).

The more complex the agent, have a wider range of modes of regulation and different levels of regulation. All the different regulatory mechanisms is a hierarchy and each level acts as "referee" on the regulatory mechanisms of the lower levels.

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The "natural autonomous agents" (ie, animals) have a sufficient number of automatic mechanisms of internal regulation that will ensure their survival, at least for a relatively long period [François, 2005].

The "natural autonomous intelligent agents" (ie, human beings, as individuals or as groups) acquired, with the neo-cortex of the brain-the ability to speak on some automation of the regulations to modify. It is what is commonly known as "controls" [François, 2005].

The "autonomous artificial intelligent agents" (ie, intelligent robots) are, in essence, complex systems that have a precise mechanical structure polyarticulated governed by a sophisticated electronic control system.
robot
The key is the government of each of its components, so as to measure, monitor and modify, with continuity and speed-all the variables involved (limb movement, motor speed, body position , fluid pressure, acceleration of the mass) as a function of the goal and the environment in which it is immersed [Moriello, 2005 p. 172 / 3].

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Regardless of its kind, and Broadly, the robots are made of different subsystems [Moriello, 2005, p. 172 / 3]:

• The "structure or chassis" is responsible for shaping the robot and sustain their components. May consist of many materials (plastics, metals, etc..) And have the most varied forms, but usually consists of rigid parts connected by joints. You can be like: "endoskeleton" (where the structure is internal and other external components) and "exoskeleton" (where the structure is external and the other covers elements).

· The "sensors" are systems which allow the robot to perceive certain phenomena or events in their local environment. Is the robotic equivalent of human sensory systems. Can be "internal" or "proprioceptive" (provides information about the internal state of the robot itself) and "external" or "exteroceptive" (provides information about the environment surrounding the robot).

· The "effector" are systems which allow the robot to interact with their local environment. Is the robotic equivalent of the human motor system. May be: "locomotion" (is the ability to move from one place to another) and "manipulation" (is the ability to handle objects).

· The "drivers" or "control circuitry" allow the proper administration of the entire system, continuously coupling the skills of perception and action: receive sensor data and send commands to the effectors. Is the robotic equivalent of the human brain.

• The "energy source" is the system responsible for feeding all parts of the robot. Might be "battery" or "batteries" (if the robot has to move independently), "drive" (if the robot is fixed, or moves a short distance) and "solar cells" (if the robot is very low or if it moves through interplanetary space.)

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Intelligent Robots Architecture "three layers"



Obviously, the complexity of the environment has a close relationship with the complexity of the control system that governs the behavior of the machine. Indeed, if the robot has to react quickly and intelligently in a dynamic and challenging environment, the problem becomes very difficult to control. If the robot, however, need not respond quickly, reducing the complexity required to develop the [Mataric, 2002].

The "three-tier architecture" can consider three different kinds of processes [Davis, 1998] [Sloman, 1996], similar to the neurological hypothesis MacLean triune brain or Freud's psychological hypothesis of the interaction between the "It" (or collection of impulses instinctive), the "Super-I" (which includes the objectives and social prohibitions high level) and "Yo" (which resolves conflicts or deleted them) [Minsky, 2000].

is likely that these processes operate in parallel and through many types of interaction. Are basically three (Moriello, 2005, p. 194 / 5):

· "Reactive": This is the most bajo y equivale a las partes más viejas y primitivas del cerebro humano (el paleoencéfalo o cerebro reptiliano). La información se adquiere por medio de los sensores externos e internos y se traduce en órdenes para los efectores. Se trata de procesos muy rápidos, o inmediatos, que permiten una respuesta directa a los eventos sensoriales.

· “Deliberativo”: Es el nivel intermedio y equivale a las partes un poco más modernas del cerebro humano (el mesencéfalo o cerebro mamífero). Se podría decir que es el verdadero corazón del sistema, ya que provee las capacidades de razonamiento, planificación y resolución de problemas. Son aquellos procesos que desempeñan un papel importante in what is known as "thinking" over other processes related to the management of low-level actions.

· "Reflective" is the highest level and is equivalent to the most recent human brain (the neocortex or brain neomamífero). Allows the monitoring, evaluation, and some control of internal processes and the provision of typically human capabilities (such as introspection, learning and explicit decisions to redirect the attention.) It's basically learning mechanisms, one way or another, permeates the entire architecture.