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| public:t-720-atai:atai-19:readings [2019/09/02 09:26] – thorisson | public:t-720-atai:atai-19:readings [2024/04/29 13:33] (current) – external edit 127.0.0.1 |
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| **As you read papers from each of the following categories I want you ask yourself a few questions:** | **As you read papers from each of the following categories I want you ask yourself a few questions:** |
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| * For each category X, ask: | * For each paper in each category X, ask yourself: |
| * What is X? | * What is X? |
| * How does the human mind do X? | * How does the human mind do X? |
| * Do current computers do X? | * Do current computers do X? |
| * ...and ... | * ...and ... |
| * Do we need X to create a machine that rivals the ability of humans to do X? | * Do we need (to replicate or capture) what the human mind does to achieve X to create a machine that rivals the ability of humans to do X? |
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| If you can answer them satisfactorily when you're done reading you're good! Even if you can't you'll be fine if you: Write down the discrepacies and //bring them to class in the form of questions//. There is no such thing as a 'stupid question' when you're learning something new. | If you can answer them satisfactorily when you're done reading you're good! Even if you can't you'll be fine if you: Write down the discrepacies and //bring them to class in the form of questions//. There is no such thing as a 'stupid question' when you're learning something new. |
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| ===== Intelligence ===== | ===== Intelligence ===== |
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| * [[http://consc.net/papers/emergence.pdf|Strong and Weak Emergence]] by D. Chalmers | * [[http://consc.net/papers/emergence.pdf|Strong and Weak Emergence]] by D. Chalmers |
| * Animals //(you are encouraged to find other material on these topics - please let instructor know if you find some good stuff)//. | * Animals //(you are encouraged to find other material on these topics - please let instructor know if you find some good stuff)//. |
| * [[https://www.youtube.com/watch?v=dKvVaRlz0Y4|Alex the Parrot]] on YouTube (video repeats halfway). [[https://en.wikipedia.org/wiki/Alex_(parrot)|Alex on Wikipedia]] | | * [[https://www.youtube.com/watch?v=dKvVaRlz0Y4|Alex the Parrot]] on YouTube (video repeats halfway). [[https://en.wikipedia.org/wiki/Alex_(parrot)|Alex on Wikipedia]] |
| * [[https://www.youtube.com/watch?v=SNuZ4OE6vCk|Koko the Gorilla]] on YouTube. [[https://en.wikipedia.org/wiki/Koko_(gorilla)|Koko on Wikipedia]] | | * [[https://www.youtube.com/watch?v=SNuZ4OE6vCk|Koko the Gorilla]] on YouTube. [[https://en.wikipedia.org/wiki/Koko_(gorilla)|Koko on Wikipedia]] |
| | * [[https://www.youtube.com/watch?v=exsrX6qsKkA|Bumblebees learn by observation]] on YouTube. [[https://www.researchgate.net/publication/272748457_Information_transfer_beyond_the_waggle_dance_Observational_learning_in_bees_and_flies|Paper on Bumblebees learning by observation]] by Loukola et al. |
| * [[https://apple.news/AQEvvY_wbRdqE1J-3MU_6WQ|Why Aren't Elephants Smarter Than Humans Since Their Brains Are Bigger?]] by Fabian van den Berg | * [[https://apple.news/AQEvvY_wbRdqE1J-3MU_6WQ|Why Aren't Elephants Smarter Than Humans Since Their Brains Are Bigger?]] by Fabian van den Berg |
| * [[https://www.youtube.com/watch?v=BG-0Bpe0J34|Parrots vs. Children]] BBC Earth on YouTube | * [[https://www.youtube.com/watch?v=BG-0Bpe0J34|Parrots vs. Children]] BBC Earth on YouTube |
| * [[http://www.gatsby.ucl.ac.uk/~dayan/papers/dw01.pdf|Reinforcement Learning in the Encyclopedia of Cognitive Science]] by Peter Dayan and Christopher Watkins. | * [[http://www.gatsby.ucl.ac.uk/~dayan/papers/dw01.pdf|Reinforcement Learning in the Encyclopedia of Cognitive Science]] by Peter Dayan and Christopher Watkins. |
| * [[http://www.ualberta.ca/~szepesva/RLBook.html|Algorithms for Reinforcement Learning]] by Csaba Szepesvári (2010) is a much more recent, shorter book that discusses the strengths and weaknesses of various RL algorithms. See also: [[http://incompleteideas.net/sutton/RL-FAQ.html|Rich Sutton's FAQ]]. | * [[http://www.ualberta.ca/~szepesva/RLBook.html|Algorithms for Reinforcement Learning]] by Csaba Szepesvári (2010) is a much more recent, shorter book that discusses the strengths and weaknesses of various RL algorithms. See also: [[http://incompleteideas.net/sutton/RL-FAQ.html|Rich Sutton's FAQ]]. |
| * [[https://en.wikipedia.org/wiki/Deep_learning|Deep learning on Wikipedia]] (Chapters: Intro, Overview, and Neural Networks). | * [[https://en.wikipedia.org/wiki/Deep_learning|Deep learning on Wikipedia]] (Sections: Intro, Overview, and Neural Networks). |
| * [[https://www.youtube.com/watch?v=2pWv7GOvuf0|Introduction to RL]] video by D. Silvers. | * [[https://www.youtube.com/watch?v=2pWv7GOvuf0|Introduction to RL]] video by D. Silvers. |
| | * [[https://en.wikibooks.org/wiki/Control_Systems/System_Metrics|Control systems: 'Type' and 'order']] on Wikibooks |
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| ==== Introductory Material - Constructionist AI [ 2,3 ] ==== | ==== Introductory Material - Constructionist AI [ 2,3 ] ==== |
| * [[http://people.csail.mit.edu/brooks/papers/how-to-build.pdf|How to Build Complete Creatures Rather than Isolated Cognitive Simulators]] by Rodney Brooks | * [[http://people.csail.mit.edu/brooks/papers/how-to-build.pdf|How to Build Complete Creatures Rather than Isolated Cognitive Simulators]] by Rodney Brooks |
| * [[http://alumni.media.mit.edu/%7Ekris/ftp/IJAAI.pdf|A Mind Model for Multimodal Communicative Creatures and Humanoids]] by Thórisson, K. R. | * [[http://alumni.media.mit.edu/%7Ekris/ftp/IJAAI.pdf|A Mind Model for Multimodal Communicative Creatures and Humanoids]] by Thórisson, K. R. |
| | * [[http://www.artificialhumancompanions.com/robot-mind-robot-body-whatever-happened-subsumption-architecture/|Whatever happened to the subsumption architecture?]] by Simon Birrell |
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| ==== Limitations of Constructionist AI [ 2,4 ] ==== | ==== Limitations of Constructionist AI [ 2,4 ] ==== |
| * [[http://alumni.media.mit.edu/~kris/ftp/AGI16_understanding.pdf|About Understanding]] by K. R. Thorisson et al. | * [[http://alumni.media.mit.edu/~kris/ftp/AGI16_understanding.pdf|About Understanding]] by K. R. Thorisson et al. |
| * [[http://alumni.media.mit.edu/~kris/ftp/IJCAI17-EGPAI-EvaluatingUnderstanding.pdf|Evaluating Understanding]] by K.R. Thórisson & J. Bieger | * [[http://alumni.media.mit.edu/~kris/ftp/IJCAI17-EGPAI-EvaluatingUnderstanding.pdf|Evaluating Understanding]] by K.R. Thórisson & J. Bieger |
| * [[http://alumni.media.mit.edu/~kris/ftp/AGI17_Understanding&CommonSense.pdf|Understanding & Common Sense]] by K. R. Thórisson & J. Bieger | * [[http://alumni.media.mit.edu/~kris/ftp/AGI17_Understanding&CommonSense.pdf|Understanding & Common Sense]] by K. R. Thórisson & D. Kremelberg |
| * [[http://alumni.media.mit.edu/~kris/ftp/AGI17-UUW-DoMachinesUnderstand.pdf|Do Machines Understand? A Short Review of Understanding & Common Sense in Artificial Intelligence]] by K.R. Thórisson & D. Kremelberg | * [[http://alumni.media.mit.edu/~kris/ftp/AGI17-UUW-DoMachinesUnderstand.pdf|Do Machines Understand? A Short Review of Understanding & Common Sense in Artificial Intelligence]] by K.R. Thórisson & D. Kremelberg |
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| * [[http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching.html|Advanced Topics: RL]] by David Silver is a more in-depth, modern RL course from one of the people who worked on Google DeepMind's Atari playing system that received a lot of (media) attention. | * [[http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching.html|Advanced Topics: RL]] by David Silver is a more in-depth, modern RL course from one of the people who worked on Google DeepMind's Atari playing system that received a lot of (media) attention. |
| * [[http://videolectures.net/nips09_littman_mbrl/|Model-Based Reinforcement Learning]] is a tutorial given by Michael Littman at NIPS'09 about model-based RL, which is a lot less common than model-free RL, but not less interesting. | * [[http://videolectures.net/nips09_littman_mbrl/|Model-Based Reinforcement Learning]] is a tutorial given by Michael Littman at NIPS'09 about model-based RL, which is a lot less common than model-free RL, but not less interesting. |
| | * [[http://link.springer.com/chapter/10.1007/978-3-642-39521-5_13#page-1|Resource-Bounded Machines are Motivated to be Effective, Efficient & Curious]] by B. Steunebrink |
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| === Deep Learning [ 0,1 ]=== | === Deep Learning [ 0,1 ]=== |
