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Readme file for Structured Systems Analysis

Description

This readme file contains details of links to all the Readme file for Structured Systems Analysis module's material held on Jorum and information about the module as well.

Subjects

ukoer | current logical data flow diagram example | current logical data flow diagram exercise | current logical data flow diagram teaching guide | current logical data flow diagram video lecture | current logical data flow diagram | current logical data flow diagrams example | current logical data flow diagrams exercise | current logical data flow diagrams teaching guide | current logical data flow diagrams video lecture | current logical data flow diagrams | current logical dfd example | current logical dfd exercise | current logical dfd teaching guide | current logical dfd video lecture | current logical dfd | current logical dfds example | current logical dfds exercise | current logical dfds lecture | current logical dfds teaching guide | data dictionary example | data dictionary exercise | data dictionary lecture | data dictionary reading material | data dictionary teaching guide | data dictionary video lecture | data dictionary | data example | data exercise | data flow diagram example | data flow diagram exercise | data flow diagram reading material | data flow diagram teaching guide | data flow diagram video lecture | data flow diagram | data flow diagrams example | data flow diagrams exercise | data flow diagrams reading material | data flow diagrams teaching guide | data flow diagrams video lecture | data flow diagrams | data reading material | data teaching guide | data video lecture | data | decision table and tree example | decision table and tree exercise | decision table and tree reading material | decision table and tree teaching guide | decision table and tree video lecture | decision table and tree | decision table example | decision table exercise | decision table reading material | decision table teaching guide | decision table video lecture | decision table | decision tables and trees example | decision tables and trees lecture | decision tables and trees reading material | decision tables example | decision tables exercise | decision tables reading material | decision tables teaching guide | decision tables video lecture | decision tables | decision tree example | decision tree exercise | decision tree reading material | decision tree teaching guide | decision tree video lecture | decision tree | decision trees and decision tables exercise | decision trees and decision tables teaching guide | decision trees and decision tables video lecture | decision trees and decision tables | decision trees example | decision trees exercise | decision trees reading material | decision trees teaching guide | decision trees video lecture | decision trees | dfd example | dfd exercise | dfd reading material | dfd teaching guide | dfd video lecture | dfd | dfds example | dfds exercise | dfds reading material | dfds teaching guide | dfds video lecture | dfds | exploding data flow diagrams example | exploding data flow diagrams exercise | exploding data flow diagrams reading material | exploding data flow diagrams teaching guide | exploding data flow diagrams | exploding dfd example | exploding dfd exercise | exploding dfd reading material | exploding dfd teaching guide | exploding dfd | logical data flow diagram example | logical data flow diagram exercise | logical data flow diagram reading material | logical data flow diagram teaching guide | logical data flow diagram video lecture | logical data flow diagram | logical data flow diagrams example | logical data flow diagrams exercise | logical data flow diagrams teaching guide | logical data flow diagrams video lecture | logical data flow diagrams | logical dfd example | logical dfd exercise | logical dfd reading material | logical dfd teaching guide | logical dfd video lecture | logical dfd | logical dfds example | logical dfds exercise | logical dfds reading material | logical dfds teaching guide | logical dfds video lecture | logical dfds | project management practical | project management reading material | project management task guide | project management teaching guide | project management | quality management | quality managment reading material | quality managment task guide | required logical data flow diagram example | required logical data flow diagram exercise | required logical data flow diagram reading material | required logical data flow diagram teaching guide | required logical data flow diagram video lecture | required logical data flow diagram | required logical data flow diagrams example | required logical data flow diagrams exercise | required logical data flow diagrams reading material | required logical data flow diagrams teaching guide | required logical data flow diagrams video lecture | required logical data flow diagrams | required logical dfd example | required logical dfd exercise | required logical dfd reading material | required logical dfd teaching guide | required logical dfd video lecture | required logical dfd | required logical dfds example | required logical dfds exercise | required logical dfds lecture | required logical dfds reading material | required logical dfds teaching guide | structured chart example | structured chart exercise | structured chart reading material | structured chart teaching guide | structured chart video lecture | structured chart | structured charts example | structured charts exercise | structured charts lecture | structured charts reading material | structured charts teaching guide | structured charts video lecture | structured charts | structured english example | structured english exercise | structured english lecture | structured english teaching guide | structured english video lecture | structured english | structured system analysis example | structured system analysis exercise | structured system analysis lecture | structured system analysis practical | structured system analysis reading material | structured system analysis task guide | structured system analysis teaching guide | structured system analysis video lecture | structured system analysis | structured systems analysis example | structured systems analysis exercise | structured systems analysis lecture | structured systems analysis practical | structured systems analysis reading material | structured systems analysis task guide | structured systems analysis teaching guide | structured systems analysis video lecture | structured systems analysis | structured walkthroughs reading material | system analysis example | system analysis exercise | system analysis lecture | system analysis practical | system analysis reading material | system analysis task guide | system analysis teaching guide | system analysis video lecture | system analysis | systems analysis example | systems analysis exercise | systems analysis lecture | systems analysis practical | systems analysis reading material | systems analysis task guide | systems analysis teaching guide | systems analysis video lecture | systems analysis | techniques in methods lecture | techniques in methods teaching guide | techniques in methods | uml | univeral modelling language lecture | univeral modelling language | universal modeling language lecture | universal modeling language | current logical dfds video lecture | current logical dfds | exploding dfds example | exploding dfds exercise | exploding dfds reading material | exploding dfds teaching guide | exploding dfds | levelling dfds example | levelling dfds exercise | levelling dfds reading material | levelling dfds teaching guide | levelling dfds | required logical dfds video lecture | required logical dfds | uml lecture | Computer science | I100

License

Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales http://creativecommons.org/licenses/by-nc-sa/2.0/uk/ http://creativecommons.org/licenses/by-nc-sa/2.0/uk/

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Structured Systems Analysis - Decision Tables and Trees

Description

This video lecture forms part of the "Decision Tables and Trees" topic in the Structured Systems Analysis module.

Subjects

decision tables and trees lecture | decision trees | decision tables | decision trees and decision tables | systems analysis | structured systems analysis | system analysis | structured system analysis | decision table | decision tree | decision table and tree | decision trees video lecture | decision tables video lecture | decision trees and decision tables video lecture | systems analysis video lecture | structured systems analysis video lecture | system analysis video lecture | structured system analysis video lecture | decision table video lecture | decision tree video lecture | decision table and tree video lecture | Computer science | I100

License

Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales http://creativecommons.org/licenses/by-nc-sa/2.0/uk/ http://creativecommons.org/licenses/by-nc-sa/2.0/uk/

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Unidentified residence - Tallahassee Unidentified residence - Tallahassee

Description

Subjects

trees | trees | homes | homes | florida | florida | tallahassee | tallahassee | oaktrees | oaktrees | dilapidations | dilapidations | woodenhomes | woodenhomes

License

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Structured Systems Analysis - Decision Tables and Trees

Description

This teaching guide forms part of the "Decision Tables and Trees" topic in the Structured Systems Analysis module.

Subjects

ukoer | decision trees | decision tables | decision trees and decision tables | systems analysis | structured systems analysis | system analysis | structured system analysis | decision table | decision tree | decision table and tree | decision trees teaching guide | decision tables teaching guide | decision trees and decision tables teaching guide | systems analysis teaching guide | structured systems analysis teaching guide | system analysis teaching guide | structured system analysis teaching guide | decision table teaching guide | decision tree teaching guide | decision table and tree teaching guide | Computer science | I100

License

Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales http://creativecommons.org/licenses/by-nc-sa/2.0/uk/ http://creativecommons.org/licenses/by-nc-sa/2.0/uk/

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Structured Systems Analysis - Decision Tables and Trees

Description

This example forms part of the "Decision Tables and Trees" topic in the Structured Systems Analysis module.

Subjects

ukoer | decision tables and trees example | decision trees | decision tables | decision trees and decision tables | systems analysis | structured systems analysis | system analysis | structured system analysis | decision table | decision tree | decision table and tree | decision trees example | decision tables example | systems analysis example | structured systems analysis example | system analysis example | structured system analysis example | decision table example | decision tree example | decision table and tree example | Computer science | I100

License

Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales http://creativecommons.org/licenses/by-nc-sa/2.0/uk/ http://creativecommons.org/licenses/by-nc-sa/2.0/uk/

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Structured Systems Analysis - Decision Tables and Trees

Description

This reading material forms part of the "Decision Tables and Trees" topic in the Structured Systems Analysis module.

Subjects

ukoer | decision tables and trees reading material | decision trees | decision tables | decision trees and decision tables | systems analysis | structured systems analysis | system analysis | structured system analysis | decision table | decision tree | decision table and tree | decision trees reading material | decision tables reading material | systems analysis reading material | structured systems analysis reading material | system analysis reading material | structured system analysis reading material | decision table reading material | decision tree reading material | decision table and tree reading material | Computer science | I100

License

Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales http://creativecommons.org/licenses/by-nc-sa/2.0/uk/ http://creativecommons.org/licenses/by-nc-sa/2.0/uk/

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Structured Systems Analysis - Decision Tables and Trees

Description

This exercise forms part of the "Decision Tables and Trees" topic in the Structured Systems Analysis module.

Subjects

ukoer | decision trees | decision tables | decision trees and decision tables | systems analysis | structured systems analysis | system analysis | structured system analysis | decision table | decision tree | decision table and tree | decision trees exercise | decision tables exercise | decision trees and decision tables exercise | systems analysis exercise | structured systems analysis exercise | system analysis exercise | structured system analysis exercise | decision table exercise | decision tree exercise | decision table and tree exercise | Computer science | I100

License

Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales http://creativecommons.org/licenses/by-nc-sa/2.0/uk/ http://creativecommons.org/licenses/by-nc-sa/2.0/uk/

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Structured Systems Analysis - Decision Tables and Trees

Description

This exercise forms part of the "Decision Tables and Trees" topic in the Structured Systems Analysis module.

Subjects

ukoer | decision trees | decision tables | decision trees and decision tables | systems analysis | structured systems analysis | system analysis | structured system analysis | decision table | decision tree | decision table and tree | decision trees exercise | decision tables exercise | decision trees and decision tables exercise | systems analysis exercise | structured systems analysis exercise | system analysis exercise | structured system analysis exercise | decision table exercise | decision tree exercise | decision table and tree exercise | Computer science | I100

License

Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales http://creativecommons.org/licenses/by-nc-sa/2.0/uk/ http://creativecommons.org/licenses/by-nc-sa/2.0/uk/

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18.997 Topics in Combinatorial Optimization (MIT) 18.997 Topics in Combinatorial Optimization (MIT)

Description

In this graduate-level course, we will be covering advanced topics in combinatorial optimization. We will start with non-bipartite matchings and cover many results extending the fundamental results of matchings, flows and matroids. The emphasis is on the derivation of purely combinatorial results, including min-max relations, and not so much on the corresponding algorithmic questions of how to find such objects. The intended audience consists of Ph.D. students interested in optimization, combinatorics, or combinatorial algorithms. In this graduate-level course, we will be covering advanced topics in combinatorial optimization. We will start with non-bipartite matchings and cover many results extending the fundamental results of matchings, flows and matroids. The emphasis is on the derivation of purely combinatorial results, including min-max relations, and not so much on the corresponding algorithmic questions of how to find such objects. The intended audience consists of Ph.D. students interested in optimization, combinatorics, or combinatorial algorithms.

Subjects

combinatorial optimization | combinatorial optimization | Ear decompositions | Ear decompositions | Nonbipartite matching | Nonbipartite matching | Gallai-Milgram and Bessy-Thomasse theorems on partitioning/covering graphs by directed paths/cycles | Gallai-Milgram and Bessy-Thomasse theorems on partitioning/covering graphs by directed paths/cycles | Minimization of submodular functions | Minimization of submodular functions | Matroid intersection | Matroid intersection | Polymatroid intersection | Polymatroid intersection | Jump systems | Jump systems | Matroid union | Matroid union | Matroid matching | path matchings | Matroid matching | path matchings | Packing trees and arborescences | Packing trees and arborescences | Packing directed cuts and the Lucchesi-Younger theorem | Packing directed cuts and the Lucchesi-Younger theorem | Submodular flows and the Edmonds-Giles theorem | Submodular flows and the Edmonds-Giles theorem | Graph orientation | Graph orientation | Connectivity tree and connectivity augmentation | Connectivity tree and connectivity augmentation | Multicommodity flows | Multicommodity flows | Connectivity tree | Connectivity tree | connectivity augmentation | connectivity augmentation | Gallai-Milgram Theorem | Gallai-Milgram Theorem | Bessy-Thomasse Theorem | Bessy-Thomasse Theorem | paritioning graphs | paritioning graphs | covering graphs | covering graphs | directed paths | directed paths | directed cycles | directed cycles | matroid matching | matroid matching | path matching | path matching | packing directed cuts | packing directed cuts | Luchessi-Younger Theorem | Luchessi-Younger Theorem | packing trees | packing trees | arborescences | arborescences | submodular flows | submodular flows | Edmonds-Giles Theorem | Edmonds-Giles Theorem

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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Riverside, Calif. By Mr. Taylor Riverside, Calif. By Mr. Taylor

Description

Subjects

california | california | trees | trees | palmtrees | palmtrees | roads | roads | carriages | carriages | uswest | uswest

License

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16.410 Principles of Autonomy and Decision Making (MIT) 16.410 Principles of Autonomy and Decision Making (MIT)

Description

This course surveys a variety of reasoning, optimization, and decision-making methodologies for creating highly autonomous systems and decision support aids. The focus is on principles, algorithms, and their applications, taken from the disciplines of artificial intelligence and operations research. Reasoning paradigms include logic and deduction, heuristic and constraint-based search, model-based reasoning, planning and execution, reasoning under uncertainty, and machine learning. Optimization paradigms include linear, integer and dynamic programming. Decision-making paradigms include decision theoretic planning, and Markov decision processes. This course is offered both to undergraduate (16.410) students as a professional area undergraduate subject, in the field of aerospace information This course surveys a variety of reasoning, optimization, and decision-making methodologies for creating highly autonomous systems and decision support aids. The focus is on principles, algorithms, and their applications, taken from the disciplines of artificial intelligence and operations research. Reasoning paradigms include logic and deduction, heuristic and constraint-based search, model-based reasoning, planning and execution, reasoning under uncertainty, and machine learning. Optimization paradigms include linear, integer and dynamic programming. Decision-making paradigms include decision theoretic planning, and Markov decision processes. This course is offered both to undergraduate (16.410) students as a professional area undergraduate subject, in the field of aerospace information

Subjects

autonomy | autonomy | decision | decision | decision-making | decision-making | reasoning | reasoning | optimization | optimization | autonomous | autonomous | autonomous systems | autonomous systems | decision support | decision support | algorithms | algorithms | artificial intelligence | artificial intelligence | a.i. | a.i. | operations | operations | operations research | operations research | logic | logic | deduction | deduction | heuristic search | heuristic search | constraint-based search | constraint-based search | model-based reasoning | model-based reasoning | planning | planning | execution | execution | uncertainty | uncertainty | machine learning | machine learning | linear programming | linear programming | dynamic programming | dynamic programming | integer programming | integer programming | network optimization | network optimization | decision analysis | decision analysis | decision theoretic planning | decision theoretic planning | Markov decision process | Markov decision process | scheme | scheme | propositional logic | propositional logic | constraints | constraints | Markov processes | Markov processes | computational performance | computational performance | satisfaction | satisfaction | learning algorithms | learning algorithms | system state | system state | state | state | search treees | search treees | plan spaces | plan spaces | model theory | model theory | decision trees | decision trees | function approximators | function approximators | optimization algorithms | optimization algorithms | limitations | limitations | tradeoffs | tradeoffs | search and reasoning | search and reasoning | game tree search | game tree search | local stochastic search | local stochastic search | stochastic | stochastic | genetic algorithms | genetic algorithms | constraint satisfaction | constraint satisfaction | propositional inference | propositional inference | rule-based systems | rule-based systems | rule-based | rule-based | model-based diagnosis | model-based diagnosis | neural nets | neural nets | reinforcement learning | reinforcement learning | web-based | web-based | search trees | search trees

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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16.410 Principles of Autonomy and Decision Making (MIT) 16.410 Principles of Autonomy and Decision Making (MIT)

Description

This course surveys a variety of reasoning, optimization, and decision-making methodologies for creating highly autonomous systems and decision support aids. The focus is on principles, algorithms, and their applications, taken from the disciplines of artificial intelligence and operations research. Reasoning paradigms include logic and deduction, heuristic and constraint-based search, model-based reasoning, planning and execution, reasoning under uncertainty, and machine learning. Optimization paradigms include linear, integer and dynamic programming. Decision-making paradigms include decision theoretic planning, and Markov decision processes. This course is offered both to undergraduate (16.410) students as a professional area undergraduate subject, in the field of aerospace information This course surveys a variety of reasoning, optimization, and decision-making methodologies for creating highly autonomous systems and decision support aids. The focus is on principles, algorithms, and their applications, taken from the disciplines of artificial intelligence and operations research. Reasoning paradigms include logic and deduction, heuristic and constraint-based search, model-based reasoning, planning and execution, reasoning under uncertainty, and machine learning. Optimization paradigms include linear, integer and dynamic programming. Decision-making paradigms include decision theoretic planning, and Markov decision processes. This course is offered both to undergraduate (16.410) students as a professional area undergraduate subject, in the field of aerospace information

Subjects

autonomy | autonomy | decision | decision | decision-making | decision-making | reasoning | reasoning | optimization | optimization | autonomous | autonomous | autonomous systems | autonomous systems | decision support | decision support | algorithms | algorithms | artificial intelligence | artificial intelligence | a.i. | a.i. | operations | operations | operations research | operations research | logic | logic | deduction | deduction | heuristic search | heuristic search | constraint-based search | constraint-based search | model-based reasoning | model-based reasoning | planning | planning | execution | execution | uncertainty | uncertainty | machine learning | machine learning | linear programming | linear programming | dynamic programming | dynamic programming | integer programming | integer programming | network optimization | network optimization | decision analysis | decision analysis | decision theoretic planning | decision theoretic planning | Markov decision process | Markov decision process | scheme | scheme | propositional logic | propositional logic | constraints | constraints | Markov processes | Markov processes | computational performance | computational performance | satisfaction | satisfaction | learning algorithms | learning algorithms | system state | system state | state | state | search treees | search treees | plan spaces | plan spaces | model theory | model theory | decision trees | decision trees | function approximators | function approximators | optimization algorithms | optimization algorithms | limitations | limitations | tradeoffs | tradeoffs | search and reasoning | search and reasoning | game tree search | game tree search | local stochastic search | local stochastic search | stochastic | stochastic | genetic algorithms | genetic algorithms | constraint satisfaction | constraint satisfaction | propositional inference | propositional inference | rule-based systems | rule-based systems | rule-based | rule-based | model-based diagnosis | model-based diagnosis | neural nets | neural nets | reinforcement learning | reinforcement learning | web-based | web-based | search trees | search trees

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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s wood culture

Description

Part of the Future of Crops lecture series delivered at the Oxford Botanic Gardens. Trees, woodlands and their product, wood, surround our lives. In Britain today, people that access or connect with woodlands do so through a society that cherishes the beauty of the treescape and the wildlife it supports. A new dawn is breaking for forestry. Can we manage forests for carbon, grow fibre for wood heat and energy, and adapt to climate change, while continuing to meet existing objectives from UK forests? The forestry sector needs to engage with society. The Sylva Foundation's OneOak project aims to do this through science and art, focussing on the full life story of one oak tree. Wales; http://creativecommons.org/licenses/by-nc-sa/2.0/uk/

Subjects

ecology | gardening | food | botanic gardens | woodland | trees | one oak project | ecology | gardening | food | botanic gardens | woodland | trees | one oak project | 2010-12-29

License

http://creativecommons.org/licenses/by-nc-sa/2.0/uk/

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View of Mitla Church built in the Ruins View of Mitla Church built in the Ruins

Description

Subjects

trees | trees | plants | plants | mountains | mountains | buildings | buildings | de | de | landscapes | landscapes | ruins | ruins | san | san | pablo | pablo | churches | churches | mosaics | mosaics | villa | villa | oaxaca | oaxaca | walls | walls | palaces | palaces | mitla | mitla

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Part of Mitla ruins surround the Church Part of Mitla ruins surround the Church

Description

Subjects

trees | trees | plants | plants | mountains | mountains | buildings | buildings | de | de | landscapes | landscapes | ruins | ruins | san | san | mila | mila | pablo | pablo | churches | churches | mosaics | mosaics | villa | villa | oaxaca | oaxaca | walls | walls | palaces | palaces

License

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6.832 Underactuated Robotics (MIT) 6.832 Underactuated Robotics (MIT)

Description

Includes audio/video content: AV lectures. Robots today move far too conservatively, using control systems that attempt to maintain full control authority at all times. Humans and animals move much more aggressively by routinely executing motions which involve a loss of instantaneous control authority. Controlling nonlinear systems without complete control authority requires methods that can reason about and exploit the natural dynamics of our machines. This course discusses nonlinear dynamics and control of underactuated mechanical systems, with an emphasis on machine learning methods. Topics include nonlinear dynamics of passive robots (walkers, swimmers, flyers), motion planning, partial feedback linearization, energy-shaping control, analytical optimal control, reinforcement learning/a Includes audio/video content: AV lectures. Robots today move far too conservatively, using control systems that attempt to maintain full control authority at all times. Humans and animals move much more aggressively by routinely executing motions which involve a loss of instantaneous control authority. Controlling nonlinear systems without complete control authority requires methods that can reason about and exploit the natural dynamics of our machines. This course discusses nonlinear dynamics and control of underactuated mechanical systems, with an emphasis on machine learning methods. Topics include nonlinear dynamics of passive robots (walkers, swimmers, flyers), motion planning, partial feedback linearization, energy-shaping control, analytical optimal control, reinforcement learning/a

Subjects

underactuated robotics | underactuated robotics | actuated systems | actuated systems | nonlinear dynamics | nonlinear dynamics | simple pendulum | simple pendulum | optimal control | optimal control | double integrator | double integrator | quadratic regulator | quadratic regulator | Hamilton-Jacobi-Bellman sufficiency | Hamilton-Jacobi-Bellman sufficiency | minimum time control | minimum time control | acrobot | acrobot | cart-pole | cart-pole | partial feedback linearization | partial feedback linearization | energy shaping | energy shaping | policy search | policy search | open-loop optimal control | open-loop optimal control | trajectory stabilization | trajectory stabilization | iterative linear quadratic regulator | iterative linear quadratic regulator | differential dynamic programming | differential dynamic programming | walking models | walking models | rimless wheel | rimless wheel | compass gait | compass gait | kneed compass gait | kneed compass gait | feedback control | feedback control | running models | running models | spring-loaded inverted pendulum | spring-loaded inverted pendulum | Raibert hoppers | Raibert hoppers | motion planning | motion planning | randomized motion planning | randomized motion planning | rapidly-exploring randomized trees | rapidly-exploring randomized trees | probabilistic road maps | probabilistic road maps | feedback motion planning | feedback motion planning | planning with funnels | planning with funnels | linear quadratic regulator | linear quadratic regulator | function approximation | function approximation | state distribution dynamics | state distribution dynamics | state estimation | state estimation | stochastic optimal control | stochastic optimal control | aircraft | aircraft | swimming | swimming | flapping flight | flapping flight | randomized policy gradient | randomized policy gradient | model-free value methods | model-free value methods | temporarl difference learning | temporarl difference learning | Q-learning | Q-learning | actor-critic methods | actor-critic methods

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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önköping, Småland, Sweden

Description

Subjects

trees | cliff | baretrees | riksantikvarieämbetet | theswedishnationalheritageboard

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People riding a motorized omnibus - Daytona Beach, Florida People riding a motorized omnibus - Daytona Beach, Florida

Description

Subjects

buses | buses | florida | florida | palmtrees | palmtrees | daytonabeach | daytonabeach | automobiles | automobiles | omnibus | omnibus | chauffeurs | chauffeurs

License

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Machine Learning I Machine Learning I

Description

The main goals of this course are: to introduce the basic concepts of Machine Learning and Big Data Machine Learning; to describe the main areas, techniques, and processes in Machine Learning; to introduce some of the main tools in (Big Data) Machine Learning The main goals of this course are: to introduce the basic concepts of Machine Learning and Big Data Machine Learning; to describe the main areas, techniques, and processes in Machine Learning; to introduce some of the main tools in (Big Data) Machine Learning

Subjects

Nearest neighbours | Nearest neighbours | Models for regression | Models for regression | MLLIB | MLLIB | Gradient Boosting | Gradient Boosting | Bagging | Bagging | Hyper-parameter optimization | Hyper-parameter optimization | Pyspark | Pyspark | Large scale machine learning | Large scale machine learning | Boosting | Boosting | Spark | Spark | 2016 | 2016 | Random Forests | Random Forests | Machine learning | Machine learning | Decision / regression trees and rules | Decision / regression trees and rules | Feature selection | Feature selection | Model evaluation | Model evaluation | Feature transformation | Feature transformation | ML | ML | Basic pipeline | Basic pipeline | Models for classification | Models for classification | MapReduce | MapReduce | C. Computacion e Inteligencia Artificial | C. Computacion e Inteligencia Artificial | Dimensionality reduction | Dimensionality reduction

License

Copyright 2015, UC3M http://creativecommons.org/licenses/by-nc-sa/4.0/

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8.592J Statistical Physics in Biology (MIT) 8.592J Statistical Physics in Biology (MIT)

Description

Statistical Physics in Biology is a survey of problems at the interface of statistical physics and modern biology. Topics include: bioinformatic methods for extracting information content of DNA; gene finding, sequence comparison, and phylogenetic trees; physical interactions responsible for structure of biopolymers; DNA double helix, secondary structure of RNA, and elements of protein folding; considerations of force, motion, and packaging; protein motors, membranes. We also look at collective behavior of biological elements, cellular networks, neural networks, and evolution. Statistical Physics in Biology is a survey of problems at the interface of statistical physics and modern biology. Topics include: bioinformatic methods for extracting information content of DNA; gene finding, sequence comparison, and phylogenetic trees; physical interactions responsible for structure of biopolymers; DNA double helix, secondary structure of RNA, and elements of protein folding; considerations of force, motion, and packaging; protein motors, membranes. We also look at collective behavior of biological elements, cellular networks, neural networks, and evolution.

Subjects

Bioinformatics | Bioinformatics | DNA | DNA | gene finding | gene finding | sequence comparison | sequence comparison | phylogenetic trees | phylogenetic trees | biopolymers | biopolymers | DNA double helix | DNA double helix | secondary structure of RNA | secondary structure of RNA | protein folding | protein folding | protein motors | protein motors | membranes | membranes | cellular networks | cellular networks | neural networks | neural networks | evolution | evolution

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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Le Pont des Trous, Tournai, Belgium Le Pont des Trous, Tournai, Belgium

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bridge | bridge | trees | trees | sky | sky | water | water | riksantikvarieämbetet | riksantikvarieämbetet | theswedishnationalheritageboard | theswedishnationalheritageboard

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Coconut grove in Lake Worth. Coconut grove in Lake Worth Coconut grove in Lake Worth. Coconut grove in Lake Worth

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florida | florida | coconutgrove | coconutgrove | palms | palms | trees | trees | cyanotypes | cyanotypes | groves | groves | coconutpalms | coconutpalms

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Apartment building in Country Club Estates - Miami Springs Apartment building in Country Club Estates - Miami Springs

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florida | florida | palmtrees | palmtrees | apartmentbuildings | apartmentbuildings | miamisprings | miamisprings

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8.592J Statistical Physics in Biology (MIT) 8.592J Statistical Physics in Biology (MIT)

Description

Statistical Physics in Biology is a survey of problems at the interface of statistical physics and modern biology. Topics include: bioinformatic methods for extracting information content of DNA; gene finding, sequence comparison, and phylogenetic trees; physical interactions responsible for structure of biopolymers; DNA double helix, secondary structure of RNA, and elements of protein folding; considerations of force, motion, and packaging; protein motors, membranes. We also look at collective behavior of biological elements, cellular networks, neural networks, and evolution. Statistical Physics in Biology is a survey of problems at the interface of statistical physics and modern biology. Topics include: bioinformatic methods for extracting information content of DNA; gene finding, sequence comparison, and phylogenetic trees; physical interactions responsible for structure of biopolymers; DNA double helix, secondary structure of RNA, and elements of protein folding; considerations of force, motion, and packaging; protein motors, membranes. We also look at collective behavior of biological elements, cellular networks, neural networks, and evolution.

Subjects

8.592 | 8.592 | HST.452 | HST.452 | Statistical physics | Statistical physics | Bioinformatics | Bioinformatics | DNA | DNA | gene finding | gene finding | sequence comparison | sequence comparison | phylogenetic trees | phylogenetic trees | biopolymers | biopolymers | DNA double helix | DNA double helix | secondary structure of RNA | secondary structure of RNA | protein folding | protein folding | protein motors | protein motors | membranes | membranes | cellular networks | cellular networks | neural networks | neural networks | evolution | evolution

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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Five Year Old Pear in Bloom

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fruittrees | floweringtrees | texasnurserycompany

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