Machine Learning
... • An adaptive system is a set of interacting or interdependent entities, real or abstract, forming an integrated whole that together are able to respond to environmental changes or changes in the interacting parts. Feedback loops represent a key feature of adaptive systems, allowing the response to ...
... • An adaptive system is a set of interacting or interdependent entities, real or abstract, forming an integrated whole that together are able to respond to environmental changes or changes in the interacting parts. Feedback loops represent a key feature of adaptive systems, allowing the response to ...
AI and Education - Grand Challenges
... ferences [4], [5]. For example, one strand of these aims to improve AI theories, tools and techniques for knowledge representation, semantic reasoning and reasoning under uncertainty. AIED systems need to operate with uncertain, inconsistent and noisy sources of information about the learner. For ex ...
... ferences [4], [5]. For example, one strand of these aims to improve AI theories, tools and techniques for knowledge representation, semantic reasoning and reasoning under uncertainty. AIED systems need to operate with uncertain, inconsistent and noisy sources of information about the learner. For ex ...
Individual action and collective function: From sociology to multi
... These studies are often disparate. Different disciplines tend to ignore each other, although there has been cross-disciplinary work, such as AI models and cognitive studies using game theory (e.g., West & Lebiere, 2001), or sociological work incorporating psychological insights. We believe that inte ...
... These studies are often disparate. Different disciplines tend to ignore each other, although there has been cross-disciplinary work, such as AI models and cognitive studies using game theory (e.g., West & Lebiere, 2001), or sociological work incorporating psychological insights. We believe that inte ...
Document
... Objectives and Prerequisites Objectives: To become familiar with the processes and technologies used in the construction of intelligent software systems. ...
... Objectives and Prerequisites Objectives: To become familiar with the processes and technologies used in the construction of intelligent software systems. ...
Defining Student Learning Goals Office of the Provost 1
... learners are demonstrating their mastery of the objective. – What will the learners be allowed to use? – Under what conditions must the mastery of skill occur? SACS ...
... learners are demonstrating their mastery of the objective. – What will the learners be allowed to use? – Under what conditions must the mastery of skill occur? SACS ...
machine learning
... (2) When all intelligence things including humans and non-human things are inter-connected together, what will happen? What intelligence will lead to? Write your opinion. ...
... (2) When all intelligence things including humans and non-human things are inter-connected together, what will happen? What intelligence will lead to? Write your opinion. ...
UNIVERSITY MASTER´S DEGREE IN ADVANCED ARTIFICIAL
... Intelligence). The master covers in a modular way the various sub-areas of AI: Symbolic and bio-inspired methods, probabilistic reasoning, connectionism, hybrid methodologies, machine learning, artificial vision and robotics. The main learning outcomes and competencies acquired are: 1) learning the ...
... Intelligence). The master covers in a modular way the various sub-areas of AI: Symbolic and bio-inspired methods, probabilistic reasoning, connectionism, hybrid methodologies, machine learning, artificial vision and robotics. The main learning outcomes and competencies acquired are: 1) learning the ...
What we have learnt in this course
... • Difference between seeing information and making sense of it (e.g., one-time pad, zero-knowledge proofs) • Role of randomness in the above • Ability of 2 complete strangers to exchange secret information ...
... • Difference between seeing information and making sense of it (e.g., one-time pad, zero-knowledge proofs) • Role of randomness in the above • Ability of 2 complete strangers to exchange secret information ...
What we have discussed in this course COS116, Spring 2010 Adam Finkelstein
... • Difference between seeing information and making sense of it (e.g., one-time pad, zero-knowledge proofs) • Role of randomness in the above • Ability of 2 complete strangers to exchange secret information ...
... • Difference between seeing information and making sense of it (e.g., one-time pad, zero-knowledge proofs) • Role of randomness in the above • Ability of 2 complete strangers to exchange secret information ...
Applications of computer science in the life sciences
... As it visits states, an agent estimates the state’s value using the temporal difference rule Agent must exploit knowledge and explore alternatives Given enough games, the agent is very likely to discover the best action for each state ...
... As it visits states, an agent estimates the state’s value using the temporal difference rule Agent must exploit knowledge and explore alternatives Given enough games, the agent is very likely to discover the best action for each state ...
Week7
... Neural Speed • Real neuron “switching time” is on the order of milliseconds (10−3 sec) – compare to nanoseconds (10−10 sec) for current transistors – transistors are a million times faster! • But: – Biological systems can perform significant cognitive tasks (vision, language understanding) in appro ...
... Neural Speed • Real neuron “switching time” is on the order of milliseconds (10−3 sec) – compare to nanoseconds (10−10 sec) for current transistors – transistors are a million times faster! • But: – Biological systems can perform significant cognitive tasks (vision, language understanding) in appro ...
Toward a Large-Scale Characterization of the Learning Chain Reaction
... more formal analysis informed by all related disciplines will benefit artificial intelligence, psychology and neuroscience, as well as other disciplines. The study and its analysis presented here constitute a first step of its kind, paving the way to finding general scalability criteria for intellig ...
... more formal analysis informed by all related disciplines will benefit artificial intelligence, psychology and neuroscience, as well as other disciplines. The study and its analysis presented here constitute a first step of its kind, paving the way to finding general scalability criteria for intellig ...
THE PREDICATE
... [3] Planning: Another significant area of AI is planning. The problems of reasoning and planning share many common issues, but have a basic difference that originates from their definitions. The reasoning problem is mainly concerned with the testing of the satisfiability of a goal from a given set ...
... [3] Planning: Another significant area of AI is planning. The problems of reasoning and planning share many common issues, but have a basic difference that originates from their definitions. The reasoning problem is mainly concerned with the testing of the satisfiability of a goal from a given set ...
What is AI? - BYU Computer Science Students Homepage Index
... Philosophy: As a way to explore some basic and interesting (and important) philosophical questions ...
... Philosophy: As a way to explore some basic and interesting (and important) philosophical questions ...
Learning Predictive Categories Using Lifted Relational
... objects and properties, we have used two levels of categories, with in both cases three categories at the lowest level and two categories at the highest level. Figures 1 and 2 show the category membership degrees projected to first two principal components of a number of entities and properties, for ...
... objects and properties, we have used two levels of categories, with in both cases three categories at the lowest level and two categories at the highest level. Figures 1 and 2 show the category membership degrees projected to first two principal components of a number of entities and properties, for ...
LEARNING FROM OBSERVATION: Introduction Observing a task
... task and then the agent goes on to increase its performance through repeated task performance (learning from practice). Data that is collected while a human performs a task is parsed into small parts of the task called primitives. Modules are created for each primitive type that encodes the movement ...
... task and then the agent goes on to increase its performance through repeated task performance (learning from practice). Data that is collected while a human performs a task is parsed into small parts of the task called primitives. Modules are created for each primitive type that encodes the movement ...
Syllabus P140C (68530) Cognitive Science
... – Even if some units do not work, information is still preserved – because information is distributed across a network, performance degrades gradually as function of damage – (aka: robustness, fault-tolerance, graceful degradation) ...
... – Even if some units do not work, information is still preserved – because information is distributed across a network, performance degrades gradually as function of damage – (aka: robustness, fault-tolerance, graceful degradation) ...
PowerPoint-presentatie
... – Leaky learning: also update the weights of the losers (but with a smaller ) – Arrange neurons in a geometrical way: update also neighbors – Turn on input patterns gradually – Conscience mechanism: make it easier for frequent losers to win. – Add noise to input patterns ...
... – Leaky learning: also update the weights of the losers (but with a smaller ) – Arrange neurons in a geometrical way: update also neighbors – Turn on input patterns gradually – Conscience mechanism: make it easier for frequent losers to win. – Add noise to input patterns ...
Memory, Concepts, and Mental Representations
... • Under the assumption that concepts are effected by experience, concepts probably gradually develop, going through subtle changes over time. The fuzzy concept theory seems to be a better fit with this. • Having a crisp and precise definitions is not as useful as having a more fuzzy category. So eve ...
... • Under the assumption that concepts are effected by experience, concepts probably gradually develop, going through subtle changes over time. The fuzzy concept theory seems to be a better fit with this. • Having a crisp and precise definitions is not as useful as having a more fuzzy category. So eve ...
Can We Count on Neural Networks?
... models/machines that are closer to being intelligent – We therefore need to build ever more complex models of the brain that can process different sensory inputs in an integrated way ...
... models/machines that are closer to being intelligent – We therefore need to build ever more complex models of the brain that can process different sensory inputs in an integrated way ...
Synaptic Plasticity
... longer term plasticity Hebbian learning Hebb (1949) hypothesized that “ if one neuron frequently takes part in exciting another, some ...
... longer term plasticity Hebbian learning Hebb (1949) hypothesized that “ if one neuron frequently takes part in exciting another, some ...
ARTIFICIAL INTELLIGENCE, MACHINE LEARNING AND DEEP
... AI is probably what you hear about most in the media. It has become a catchy term, even spawning movies and shows about AI and robots. A wellknown example of AI is IBM’s Watson system, which beat two human champions on the television show Jeopardy! in 2011. Watson is now used for other purposes, inc ...
... AI is probably what you hear about most in the media. It has become a catchy term, even spawning movies and shows about AI and robots. A wellknown example of AI is IBM’s Watson system, which beat two human champions on the television show Jeopardy! in 2011. Watson is now used for other purposes, inc ...
Slide 1
... chosen partly because it can be segmented into sub-problems which will allow individuals to work independently and yet participate in the construction of a system complex enough to be a real landmark in the development of “pattern recognition.” Papert, S., 1966. The summer vision project. Technical ...
... chosen partly because it can be segmented into sub-problems which will allow individuals to work independently and yet participate in the construction of a system complex enough to be a real landmark in the development of “pattern recognition.” Papert, S., 1966. The summer vision project. Technical ...