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Front Matter - Assets - Cambridge
Front Matter - Assets - Cambridge

... with various degrees of intelligence are arrayed. At the other end are humans, who are able to reason, achieve goals, understand and generate language, perceive and respond to sensory inputs, prove mathematical theorems, play challenging games, synthesize and summarize information, create art and mu ...
Human Implications of Human-Robot Interaction AAAI Press Papers from the AAAI Workshop
Human Implications of Human-Robot Interaction AAAI Press Papers from the AAAI Workshop

... retains the right of first refusal to any publication (including electronic distribution) arising from this AAAI event. Please do not make any inquiries or arrangements for hardcopy or electronic publication of all or part of the papers contained in these working notes without first exploring the op ...
PPT - Sheffield Department of Computer Science
PPT - Sheffield Department of Computer Science

... What does ‘brain-style computing’ mean? Rough resemblance between units and weights in Artificial Neural Network (or ANNs) and neurons in brain and connections between them.  Individual units in a net are like real neurons.  Learning in brain similar to modifying connection ...
Chapter 14: Artificial Intelligence
Chapter 14: Artificial Intelligence

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Anthropomorphism and the social robot

... the employment of a degree of anthropomorphic, or human-like, qualities whether in form or behaviour or both. But it is not a simple problem. As discussed by Foner [5], people’s expectations based on strong anthropomorphic paradigms in HCI overly increase a user’s expectations of the system’s perfor ...
Abstract - Artificial Intelligence Applications Institute
Abstract - Artificial Intelligence Applications Institute

... mains, the following capabilities are needed to solve realistic planning problems: (1) numerical reasoning, (2) concurrent actions, (3) context –dependent effects, (4) interaction with users, (5) execution monitoring, (6) replanning, and (7) scalability. However, the main challenges in real-world do ...
Intelligent Systems 1 - IIIT
Intelligent Systems 1 - IIIT

... An agent is an entity that perceives and acts This course is about designing rational agents Abstractly, an agent is a function from percept histories to actions: f : P∗ → A For any given class of environments and tasks, we seek the agent (or class of agents) with the best performance Caveat: comput ...
OpenProblems-2011-01-21
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Dartmouth Conference: The Founding Fathers of AI Herbert Simon
Dartmouth Conference: The Founding Fathers of AI Herbert Simon

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Robots - BCCN 2009

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Learning to Parse Natural Language Commands to a

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Examining the Work and Its Later Impact
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... re-evaluation and, language and problem-solving, for instance – could in principle be constructed out of these building blocks. Call this the bubble-up theory of mind, and contrast it with the various trickle-down theories of mind, by thinkers from Rene´ Descartes to John Searle (and including, noto ...
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EXPERT SYSTEM FOR DECISION-MAKING PROBLEM

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Human Neural Systems for Face Recognition and Social

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Brain Internal Structure (2)

...  Secondary auditory area ( association) is posterior to primary area and in superior temporal gyrus (Brodmann area 22).  Sensory speech area of Wernicke is in dominant hemisphere, mainly in superior temporal gyrus, with extensions into the parietal region.  Wernicke area is connected to Broca are ...
Housekeeping with Multiple Autonomous Robots: Representation
Housekeeping with Multiple Autonomous Robots: Representation

... and a chair and the passage between the table and the chair is too narrow for the robot to pass through. • When a plan execution fails, the robots may need to find another plan by taking into account some temporal constraints. For instance, when a robot cannot move an object because it is heavy, the ...
Social Psychology and the Comic-Book Superhero: A
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... The Art Instinct as a seminal contribution to the philosophy of art; but its value does not end here. Given that evolutionary theory is itself an ongoing intellectual project, Dutton’s approach necessarily lends itself to extension and revision as new discoveries are made about the human cognitive e ...
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Functional Explanation in Information Systems

... deducing outcomes from general laws. As interpretive and qualitative approaches have become accepted, new types of explanatory knowledge have been based on interactions, processes and human intentions. Since IS artifacts are purposeful inventions intended to create new realities, the inclusion of kn ...
Game Theory and Decision Theory in Multi-Agent Systems
Game Theory and Decision Theory in Multi-Agent Systems

... in detail in [2]. In essence an MDP is an iterative set of classical decision problems. Consider a state of the world as a node in a graph. Carrying out an action in that state will result in a transition to one of a number of states, each connected to the first state by an arc, with some probabilit ...
Unsupervised Object Counting without Object Recognition
Unsupervised Object Counting without Object Recognition

... The second approach, which is not based on objectrecognition [8], [15], [16], extracts image features from an image. Examples of the image features include local variances of pixels [20] and the total area that may correspond to moving objects [16], [19], [36], [37]. Extraction of image features is ...
The Nature of the Social Agent - Digital Collections
The Nature of the Social Agent - Digital Collections

... analysis that consists of two sequences. In the first sequence, we start with a maximally capable agent and successively restrict its architecture4, i.e., its information processing capabilities, and so successively obtain a more and more realistic theory of human being (see table 1). We note that a ...
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Embodied cognitive science

For approaches to cognitive science that emphasize the embodied mind, see Embodied cognitionEmbodied Cognitive Science is an interdisciplinary field of research, the aim of which is to explain the mechanisms underlying intelligent behavior. It comprises three main methodologies: 1) the modeling of psychological and biological systems in a holistic manner that considers the mind and body as a single entity, 2) the formation of a common set of general principles of intelligent behavior, and 3) the experimental use of robotic agents in controlled environments.Embodied cognitive science borrows heavily from embodied philosophy and the related research fields of cognitive science, psychology, neuroscience and artificial intelligence. From the perspective of neuroscience, research in this field was led by Gerald Edelman of the Neurosciences Institute at La Jolla, the late Francisco Varela of CNRS in France, and J. A. Scott Kelso of Florida Atlantic University. From the perspective of psychology, research by Michael Turvey, Lawrence Barsalou and Eleanor Rosch. From the perspective of language acquisition, Eric Lenneberg and Philip Rubin at Haskins Laboratories. From the perspective of autonomous agent design, early work is sometimes attributed to Rodney Brooks or Valentino Braitenberg. From the perspective of artificial intelligence, see Understanding Intelligence by Rolf Pfeifer and Christian Scheier or How the body shapes the way we think, also by Rolf Pfeifer and Josh C. Bongard. From the perspective of philosophy see Andy Clark, Shaun Gallagher, and Evan Thompson.Turing proposed that a machine may need a human-like body to think and speak:It can also be maintained that it is best to provide the machine with the best sense organs that money can buy, and then teach it to understand and speak English. That process could follow the normal teaching of a child. Things would be pointed out and named, etc. Again, I do not know what the right answer is, but I think both approaches should be tried (Turing, 1950).↑
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