[[http://cadia.ru.is/wiki/public:t-720-atai:atai-19:main|T-720-ATAI-2019 Main]] ===== T-720-ATAI-2019 Readings & Study Material ===== //Note: PAGE UNDER CONSTRUCTION// \\ //Note: DO NOT SKIP READING THE BELOW TEXT// This material is generally ordered by specificity (both within and between headings), starting with the general topic of what intelligence is, progressing towards good old-fashioned AI (aka constructionist AI or GOFAI) and then onward towards artificial general intelligence (AGI). Within each topic the papers are ordered by importance, the most important first. The recommended minimum number of papers to be read in each category is listed in brackets [ //a,b// ] after the title, where //a// refers to the necessary mandatory number of papers to be read, and //b// refers to the //recommended// absolute minimum number (papers are ordered from most to least important, so start counting from the top). If no number is given you should read all the papers listed. The section marked //"Prerequisites"// are readings on the basics: Things you should already know. If you even have the slightest reason to think that some content in these is not already under your belt (e.g. you have neither recently taken an introductory course on AI nor a single psychology or philosophy course on intelligence) you really should read them (they are a quick read, for the most part). This means you are expected to read well over 50 papers in this course, so that comes out to **at least** 3-4 papers per week (5 recommended). //Keep at it and you'll be fine!// Note: Assigned readings should be read //before// class. There is a simple reason for that: You will have some familiarity with the subject matter which not only means you will //remember it better// but also that you can //ask questions for clarification during the lecture// and partially //steer its direction//. Reading the papers after class //is less effective//. Warning: Do not attempt to read them during class - this is absolutely the worst way to cover this material (but of course you may have it open for reference). Reading the assigned readings not at all should generally be avoided. \\ **As you read papers from each of the following categories I want you ask yourself a few questions:** * For each paper in each category X, ask yourself: * What is X? * How does the human mind do X? * Do current computers do X? * ...and ... * 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? 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. \\ \\ \\ ===== Intelligence ===== ====Prerequisites==== * [[http://en.wikipedia.org/wiki/General_intelligence_factor| The g factor]] on Wikipedia. * [[http://en.wikipedia.org/wiki/Theory_of_multiple_intelligences| Multiple theory of intelligence]] on Wikipedia. ====Key Papers==== * [[http://www.vetta.org/documents/A-Collection-of-Definitions-of-Intelligence.pdf|A Collection of Definitions of Intelligence]] by Legg & Hutter. * [[http://www.complex-systems.com/pdf/04-1-2.pdf|Evolution, Learning & Culture: Computational Metaphors for Adaptive Algorithms]] by R. K. Belew * [[http://consc.net/papers/computation.html|A Computational Foundation for the Study of Cognition]] by D. Chalmers * [[http://www.cs.bham.ac.uk/research/projects/cogaff/Sloman.kd.pdf | Architectural Requirements for Human-like Agents Both Natural and Artificial]] by Sloman, A. * [[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)//. * [[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=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://www.youtube.com/watch?v=BG-0Bpe0J34|Parrots vs. Children]] BBC Earth on YouTube * [[https://www.youtube.com/watch?v=cbSu2PXOTOc|Crow solving an 8-step puzzle]] on YouTube * [[https://www.youtube.com/watch?v=ZerUbHmuY04|Crow demonstrates causal understanding]] on YouTube * [[https://www.youtube.com/watch?v=0fiAoqwsc9g|TED talk on crow intelligence]] by John Marzluff \\ \\ ==== Definitions of Artificial Intelligence ==== ===Prerequisites=== * [[https://en.wikipedia.org/wiki/Artificial_general_intelligence| Artificial General Intelligence]] on Wikipedia. * [[http://www.iiim.is/2010/05/questions-about-artificial-intelligence/| Four Basic Questions about Artificial Intelligence]] by P. Wang. * [[http://www-formal.stanford.edu/jmc/whatisai/|What Is AI?]] by J. McCarthy. === Key Papers [ 3,5 ] === * {{/public:t-720-atai:peiwang_2019_ondefiningai_jagi.pdf|On Defining Artificial Intelligence, Journal of Artificial General Intelligence 10(2):1-37}} by Pei Wang. * [[https://www.kurzweilai.net/essentials-of-general-intelligence-the-direct-path-to-agi|Essentials of General Intelligence: The Path Towards AGI]] by P. Voss. * [[http://www.cs.bham.ac.uk/research/projects/cogaff/misc/fully-deliberative.html|Requirements for deliberative systems]] by A. Sloman -- key sections: from 8 onwards. * [[http://www.loebner.net/Prizef/TuringArticle.html|Computing Machinery and Intelligence]] by A. Turing. * [[http://cis-linux1.temple.edu/~pwang/Publication/AI_Misconceptions.pdf|Three Fundamental Misconceptions of Artificial Intelligence]] by Pei Wang. * [[http://act-r.psy.cmu.edu/wordpress/wp-content/uploads/2012/12/526FSQUERY.pdf| An integrated theory of mind]] by Anderson et al. * [[http://arxiv.org/abs/0712.3329|Universal Intelligence: A Definition of Machine Intelligence]] by Shane Legg and Marcus Hutter. \\ ===== Constructionist Systems & Methodologies ===== ====Prerequisites==== * [[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]]. * [[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://en.wikibooks.org/wiki/Control_Systems/System_Metrics|Control systems: 'Type' and 'order']] on Wikibooks ==== Introductory Material - Constructionist AI [ 2,3 ] ==== * {{:public:intro_to_software_arch.pdf| Introduction to Software Architecture}} by Garlan & Shaw. * [[http://alumni.media.mit.edu/%7Ekris/ftp/AIMag-CDM-ThorissonEtAl04.pdf| Constructionist Design Methdology]] paper by K.R. Thórisson. * [[https://en.wikipedia.org/wiki/Subsumption_architecture|Subsumption Architecture]] on Wikipedia. * [[ftp://publications.ai.mit.edu/ai-publications/pdf/AIM-864.pdf|A Robust Layered Control System for a Mobile Robot]] by R. Brooks. * [[https://en.wikipedia.org/wiki/Belief%E2%80%93desire%E2%80%93intention_software_model|BDI Architecture]] on Wikipedia. * [[https://www.aaai.org/Papers/ICMAS/1995/ICMAS95-042.pdf|BDI Agents: From Theory to Practice]] by A.S. Rao & M.P. Georgeff. * [[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://www.artificialhumancompanions.com/robot-mind-robot-body-whatever-happened-subsumption-architecture/|Whatever happened to the subsumption architecture?]] by Simon Birrell ==== Limitations of Constructionist AI [ 2,4 ] ==== * {{:public:archmismatch-icse17.pdf| Architectural Mismatch or Why it’s hard to build systems out of existing parts}} by Garlan, D., R. Allen and J. Ockerbloom. Also available [[http://www.cs.cmu.edu/afs/cs/project/able/ftp/archmismatch-icse17/archmismatch-icse17.pdf|here]]. * [[http://alumni.media.mit.edu/~kris/ftp/Thorisson-ReductioAdAbsurdum-AGI2013.pdf|Reductio ad Absurdum: On Oversimplification in Computer Science & its Pernicious Effect on Artificial Intelligence Research]] by K. R. Thórisson. * [[http://journals.isss.org/index.php/proceedings53rd/article/viewFile/1249/410|ROBERT ROSEN’S ANTICIPATORY SYSTEMS THEORY: THE ART AND SCIENCE OF THINKING AHEAD]] by J. Rosen. * [[https://aeon.co/essays/how-close-are-we-to-creating-artificial-intelligence| The very laws of physics imply that artificial intelligence must be possible. What's holding us up?]] by D. Deutch. \\ \\ ===== The Holy Grail of AI: Generality ===== ==== Overview of Artificial General Intelligence [ 4,5 ] ==== * [[http://cadia.ru.is/wiki/public:t720-atai-2012:what_is_agi|What is AGI?]] by K. R. Thórisson. * [[http://cis-linux1.temple.edu/~pwang/Publication/AGI_Aspects.pdf|Introduction: Aspects of Artificial General Intelligence]] by P. Wang & B. Goerzel (first 3 sections) * [[http://w3.sista.arizona.edu/~cohen/cs-665-spring-2010/readings/fin.arch.pdf| Cognitive architectures: Research issues and challenges]] by Langley, P., Laird, J.E., Rogers, S. * [[http://hrilab.cs.tufts.edu/publications/adamsetal12aimag.pdf|Mapping the Landscape of Human-Level Artificial General Intelligence]] by Adams et al. * [[http://goertzel.org/dynapsyc/2009/BlocksNBeadsWorld.pdf | What Must a World Be Like That a Human-Like Intelligence May Develop In It?]] by B. Goertzel. * [[http://act-r.psy.cmu.edu/wordpress/wp-content/uploads/2012/12/526FSQUERY.pdf|(ACT-R) An Integrated Theory of the Mind]] by Anderson, J. R.; Bothell, D.; Byrne, M.D.; Douglass, S.; Lebiere, C. & Qin, Y. ==== Requirements for AGI [ 3,5 ] ==== Related to: //Methodology, Cognitive Architectures// * [[https://pdfs.semanticscholar.org/4688/e564f16662838938a2d729685baab068751b.pdf?_ga=2.196493103.2038245345.1566469635-1488191987.1566469635|Cognitive Architecture Requirements for Achieving AGI]] by J.E. Laird et al. * [[http://www.cs.bham.ac.uk/research/projects/cogaff/Sloman.kd.pdf|Architectural Requirements for Human-like Agents Both Natural and Artificial]] by A. Sloman * [[http://www.isle.org/~langley/papers/final.arch.pdf| Cognitive architectures: Research issues and challenges.]] by Langley, P., Laird, J.E., Rogers, S. (2009). Cognitive Systems Research Vol 10(2), pp. 141-160. * [[http://alumni.media.mit.edu/~kris/ftp/agi-09-TransversalSkills-Thorisson-Nivel.pdf|Holistic Intelligence: Transversal Skills & Current Methodologies]] by K.R. Thórisson & E. Nivel. * [[https://iccm-conference.neocities.org/2007/files/wray__lebiere__weinstein__jha__springer__belding__best____van_parunak.pdf| Towards a Complete, Multi-level Cognitive Architecture]] by R. Wray et al. ==== Thought, Cognition, Cognitive Process/es ==== Related to: //Cognitive Architecture, Intelligence, Understanding, AI // * [[https://www.psychologytoday.com/intl/blog/consciousness-and-the-brain/201202/what-is-thought|What is Thought?]] by Ezequiel Morsella * [[https://en.wikipedia.org/wiki/Thought|Thought]] on Wikipedia. * [[https://en.wikipedia.org/wiki/Animal_cognition|Animal Cognition]] on Wikipedia. * [[https://lexfridman.com/?powerpress_pinw=3920-podcast|Podcast interview with Jeff Hawkins]] by L. Friedman * [[http://alumni.media.mit.edu/~kris/ftp/Helgason%20et%20al-AGI2013.pdf|Predictive Heuristics for Decision-Making in Real-World Environments]] by H. Helgason et al. ==== Understanding [ 3,4 ]==== Related to: //Thought, Reasoning// * [[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/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 ==== Situatedness, Embodiment [ 1,2 ] ==== Related to: //Symbols, Meaning, Autonomy, Bootstrapping // * [[http://pespmc1.vub.ac.be/riegler/papers/riegler02embodiment.pdf| When is a cognitive system embodied?]] by Riegler * [[http://cis-linux1.temple.edu/~pwang/Publication/embodiment.pdf|Does a Laptop Have a Body?]] by P. Wang. * [[http://cogprints.org/2517/1/Lindblom.pdf| Social situatedness]] by Lindblom & Ziemke ==== Autonomy [ 3,4 ]==== Related to: //Bootstrapping / Self-Programming// * [[http://tierra.aslab.upm.es/~sanz/old/docs/ISIC-2000.pdf|Fridges, Elephants, and the Meaning of Autonomy and Intelligence]] by R. Sanz et al. * [[http://alumni.media.mit.edu/~kris/ftp/AutonomyCogArchReview-ThorissonHelgason-JAGI-2012.pdf|Cognitive Architectures & Autonomy: A Comparative Review]] by K.R. Thórisson & H.P. Helgason * [[http://alumni.media.mit.edu/~kris/ftp/nivel_thorisson_replicode_AGI13.pdf|Towards a Programming Paradigm for Control Systems With High Levels of Existential Autonomy]] by E. Nivel & K. R. Thórisson. * [[https://www.researchgate.net/profile/Elena_Messina/publication/228630874_A_framework_for_autonomy_levels_for_unmanned_systems_(ALFUS)/links/0c960517a990b246b1000000.pdf|A Framework for Autonomy Levels for Unmanned Systems (ALFUS)]] by Huang et al. * [[https://www.aaai.org/ojs/index.php/aimagazine/article/view/498/434|The Emergence of Artificial Intelligence: Learning to Learn]] by P. Bock. ==== Resource Control: Attention / Self-Control / Integrated Cognitive Control [ 4,6 ] ==== Related to: //Cognitive Architecture, Learning// * [[http://cogprints.org/5941/1/ASLAB-A-2007-011.pdf|Principles of Integrated Cognitive Control]] by R. Sanz et al. * [[http://www.mindmakers.org/boards/18/topics/80|On Attention Mechanisms for AGI Architectures: A Design Proposal]] by Helgason et al.; accompanying video can be found [[https://www.youtube.com/watch?v=-EKO5u86DYM|here]]. * [[http://www.aaai.org/Papers/Symposia/Fall/2007/FS-07-01/FS07-01-025.pdf | Self-awareness in Real-time Cognitive Control Architectures]] by Sanz, R., López, I. & Hernández, C. * [[http://web.mit.edu/torralba/www/josa.pdf| A model of attention that takes global scene factors into account]] by Torralba. * [[http://alumni.media.mit.edu/~kris/ftp/nivel_thorisson_replicode_AGI13.pdf| Towards a Programming Paradigm for Control Systems with High Levels of Existential Autonomy]] by E. Nivel et al. * [[http://alumni.media.mit.edu/~kris/ftp/Helgason%20et%20al-AGI2013.pdf|Predictive Heuristics for Decision-Making in Real-World Environments]] by H. Helgason et al. * [[http://alumni.media.mit.edu/~kris/ftp/HelgasonEtAl-2014-Attention-IJCSAI10339-20140314-163624-3675-40677.pdf|Towards a General Attention Mechanism for Embedded Intelligent Systems]] by H. P. Helgason et al. * [[http://www.tcts.fpms.ac.be/publications/papers/2007/wcaa2007_mmbgbm.pdf| A three-layer model of selective attention]] by Mancas et al. * [[http://alumni.media.mit.edu/~kris/ftp/Helgason-Thorisson-AttentionForAI.pdf|Attention Capabilities for AI Systems]] by H. P. Helgason & K. R. Thórisson. ==== Self-Programming [ 4,5 ] ==== Related to: //Reasoning, Learning, Bootstrapping// * [[http://alumni.media.mit.edu/~kris/ftp/agi-09-self-programming-Nivel-Thorisson.pdf|Self-Programming: Operationalizing Autonomy]] by Nivel, E. & K. R. Thórisson. * [[https://en.wikipedia.org/wiki/Von_Neumann_universal_constructor|Von Neumann Universal Constructor]] on Wikipedia. * [[http://alumni.media.mit.edu/~kris/ftp/nivel_thorisson_replicode_AGI13.pdf|Towards a Programming Paradigm for Control Systems With High Levels of Existential Autonomy]] by E. Nivel & K. R. Thórisson. * [[http://www.iiim.is/wp/wp-content/uploads/2011/05/wang-agisp-2011.pdf|Behavioral Self-Programming by Reasoning]] by Wang, P. ==== Reasoning [ 4,6 ]==== Related to: //Thought, Cognitive Architecture, Intelligence// * [[https://pdfs.semanticscholar.org/7ca4/09b6b2569f7420d5ff481556c1c06e3e5b73.pdf|Return to Term Logic]] by Pei Wang. * [[https://cis.temple.edu/~pwang/Publication/abduction.pdf|Abduction in Non-Axiomatic Logic]] by Pei Wang. * [[https://cis.temple.edu/~pwang/Publication/induction.pdf|A New Approach for Induction: From a Non-Axiomatic Logical Point of View]] by Pei Wang * [[https://philosophynow.org/issues/106/Critical_Reasoning|Critical Reasoning]] by Marianne Talbot * [[http://cis-linux1.temple.edu/~pwang/Publication/evidence.pdf|Wason's Cards: What is Wrong?]] by P. Wang. * [[http://alumni.media.mit.edu/~kris/ftp/AEGAP18_Abduction_Deduction_Causal_Relational_Models.pdf|Abduction & Deduction With Causal-Relational Models]] by K.R. Thórisson et al. ==== (AGI) Bootstrapping / Seed A(G)I / Seed Programming [ 2,4 ] ==== Related to: //Cognitive Architecture, Intelligence// * [[http://alumni.media.mit.edu/~kris/ftp/BoundedSeedAGI_agi14.pdf|Bounded Seed-AGI]] by E. Nivel et al. * [[http://arxiv.org/pdf/1502.06512.pdf|From Seed AI to Technological Singularity via Recursively Self-Improving Software]] by R. V. Yampolskiy. * [[https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=47&cad=rja&uact=8&ved=2ahUKEwihyfrQ96PdAhXsLsAKHbNRDh4QFjAuegQISxAC&url=http%3A%2F%2Fwww.rr.cs.cmu.edu%2FCreating%2520a%2520Child%2520Machine.docx&usg=AOvVaw3ZIHWfvIoKnZF1fNf7A_EI|Creating a Child Machine: Reflections on Turing’s Proposal]] by Raj Reddy * [[https://mainatnips.github.io/mainatnips.github.io/slides/baroni-nursing-turing.pdf|Nursing Turing’s Child Machine: Towards Communication-Based Artificial Intelligence]] by Maco Baroni et al. ==== Learning ==== Related to: //Resource control, Attention, Reasoning// * [[http://alumni.media.mit.edu/~kris/ftp/AGI16_growing_recursive_self-improvers.pdf|Growing Recursive Self-Improvers]] by B. Steunebrink et al. * [[https://www.academia.edu/40043621/Cumulative_Learning|Cumulative Learning]] by K.R. Thórisson et al. * [[http://cis-linux1.temple.edu/~pwang/Publication/learning.pdf|The Logic of Learning]] by P. Wang. * [[https://www.aaai.org/ojs/index.php/aimagazine/article/view/498/434|The Emergence of Artificial Intelligence: Learning to Learn]] by P. Bock. * [[http://alumni.media.mit.edu/~kris/ftp/AGI18__Cumulative_Learning_With_Causal_Relational_Models.pdf|Cumulative Learning With Causal-Relational Models]] by K.R.Thórisson et al. ==== Artificial Pedagogy [ 2,4 ] ==== Related to: //Learning, Bootstrapping// * [[http://alumni.media.mit.edu/~kris/ftp/AGI17-pedagogical-pentagon.pdf|The Pedagogical Pentagon]] by Jordi Bieger et al. * [[http://alumni.media.mit.edu/~kris/ftp/BiegerEtAl-AGI2014-Raising_AI.pdf|Raising AI: Tutoring Matters]] by Jordi Bieger, Kristinn R. Thórisson and Deon Garrett * [[http://www.apa.org/pubs/journals/features/edu-a0037478.pdf|Matching Learning Style to Instructional Method: Effects on Comprehension]] by Rogowsky et al. * [[http://pages.cs.wisc.edu/~jerryzhu/machineteaching/pub/MachineTeachingAAAI15.pdf|Machine teaching: An inverse problem to machine learning and an approach toward optimal education]] by Xiaojin Zhu * [[http://www.martin.zinkevich.org/publications/zilles11a.pdf|Models of cooperative teaching and learning]] by Sarah Zilles, Steffen Lange, Robert Holte and Martin Zinkevich * [[http://philsci-archive.pitt.edu/9085/1/SterrettBringingUpTuringsChild-Machine6April2012ForPSAArchive.pdf|Bringing up Turing's 'Child-Machine']] by S. G. Sterrett * [[http://aamas.csc.liv.ac.uk/Proceedings/aamas2013/docs/p1053.pdf|Teaching on a Budget: Agents Advising Agents in Reinforcement Learning]] by Lisa Torrey and Matthew E. Taylor * [[http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.149.4701|Curriculum learning]] by Yoshua Bengio, Jérôme Louradour, Ronan Collobert and Jason Weston ==== AGI Methodology [ 5,6 ] ==== Related to: //Cognitive Architecture, Implemented AGI Systems // * [[/public:t_720_atai:atai-18:ConstructivistAI|Constructivist AI (CAIM)]] * [[http://alumni.media.mit.edu/~kris/ftp/Thorisson_chapt9_TFofAGI_Wang_Goertzel_2012.pdf|A New Constructivist AI: From Manual Construction to Self-Constructive Systems]] by K.R. Thórisson * {{public:i-700-abms-07-1:cantherebeascienceofcomplexity-simon-iccsproc.pdf| Can there be a science of complex systems?}} by H. A. Simon * [[http://cleamc11.vub.ac.be/books/Conant_Ashby.pdf|Every Good Regulator of a System Must be a Model of that System]] by Conant & Ashby. * [[https://pdfs.semanticscholar.org/6071/193acf08170df3226b972dadf0c1f2365ba3.pdf|A Primer For Conant & Ashby's “Good-Regulator Theorem”]] by Daniel L. Scholten * [[http://alumni.media.mit.edu/~kris/ftp/JAGI-Special-Self-Progr-Editorial-ThorissonEtAl-09.pdf|Approaches & Assumptions of Self-Programming in Achieving Artificial General Intelligence]] by Thórisson et al. * [[http://pespmc1.vub.ac.be/Papers/Cybernetics-EPST.pdf|Cybernetics and Second-Order Cybernetics]] by Heylighen, F. & C. Joslyn * [[http://www.iiim.is/2010/05/agi-cognitive-synergy-goertzel/| Does the Future of AGI Lie in Cognitive Synergy?]] by B. Goertzel \\ \\ =====Implemented AGI-Aspiring Systems===== ==== NARS [ 4,5 ] ==== * [[http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.134.4298&rep=rep1&type=pdf|From NARS to a thinking machine]] by P. Wang * [[public:t720-atai-2012:nars|What is NARS]] by K. R. Thórisson * [[http://www.cis.temple.edu/~wangp/Writing/NARS-Intro.html| Introduction to NARS]] by P. Wang * [[http://www.cis.temple.edu/~wangp/Publication/unifiedAI.pdf| NARS intro paper]] by P. Wang * [[http://www.cis.temple.edu/~wangp/demos.html| NARS demos]] by P. Wang ==== AERA [ 5,5 ]==== * [[http://alumni.media.mit.edu/~kris/ftp/PeeweeGranularity-Thorisson-Nivel-09.pdf|Achieving Artificial General Intelligence Through Peewee Granularity]] by Thórisson, K. R. & Nivel, E. * [[http://alumni.media.mit.edu/~kris/ftp/BoundedSeedAGI_agi14.pdf|Bounded Seed-AGI]] by E. Nivel et al. * [[http://alumni.media.mit.edu/%7Ekris/ftp/AAoNL-wHeadr.pdf|Autonomous Acquisition of Natural Communication]] by K. R. Thórisson et al. * [[http://alumni.media.mit.edu/~kris/ftp/AnytimeBoundedRationalityagi15_nivelEtAl.pdf|Anytime Bounded Rationality]] by E. Nivel et al. * [[http://arxiv.org/pdf/1312.6764v1.pdf|Bounded Recursive Self-Improvement]] by E. Nivel et al. * [[http://alumni.media.mit.edu/~kris/ftp/agi-09-self-programming-Nivel-Thorisson.pdf|Self-Programming: Operationalizing Autonomy]] by Nivel, E. & K. R. Thórisson. ==== Sigma [ 0,1 ] ==== * [[http://cs.usc.edu/~rosenblo/Pubs/Sigma%20AISBQ%20D.pdf|The Sigma Cognitive Architecture and System]] by P. S. Rosenbloom. ==== Open Cog [ 0,2 ] ==== * [[http://goertzel.org/dynapsyc/2009/OpenCogPrime.pdf|OPENCOG PRIME: A COGNITIVE SYNERGY BASED ARCHITECTURE FOR ARTIFICIAL GENERAL INTELLIGENCE]] by Ben Goerzel. * [[http://wiki.opencog.org/w/Getting_Started|Getting Started with Open Cog]] by Ben Goerzel. ==== Other Such Systems [ 0,3 ] ==== * Franklin, S. (2007). **(LIDA) A Foundational Architecture for Artificial General Intelligence**. Advances in Artificial General Intelligence: Concepts, Architectures and Algorithms. IOS Press, Amsterdam, The Netherlands, The Netherlands, pp. 36-54. [[http://goertzel.org/agiri06/%5B4%5D%20StanFranklin.pdf | PDF]] * Anderson, J.R. & Schunn, C.D. (2000). **Implications of the ACT-R learning theory: No magic bullets**. Advances in instructional psychology. 5:1-34. Lawrence Erlbaum [[http://www.lrdc.pitt.edu/schunn/research/papers/nomagicbullets.pdf || PDF]] * Laird, J.E.; Newell, A. & Rosenbloom, P.S. (1987). **SOAR: An architecture for general intelligence**. Artificial Intelligence, Volume 33, Issue 1, Pages 1-64 [[http://shelf2.library.cmu.edu/Tech/16128161.pdf | PDF]] * Snaider, J; McCall, R. & Franklin, S. (2011). **The LIDA framework as a general tool for AGI**. Artificial General Intelligence, Lecture Notes in Computer Science. 2011. Volume 6830/2011. pp. 133-142 [[http://ccrg.cs.memphis.edu/assets/papers/2011/The%20LIDA%20Framework%20as%20a%20General%20Tool%20for%20AGI%20final.pdf | PDF]] * J. Schmidhuber (2016). [[https://mainatnips.github.io/mainatnips.github.io/slides/schmidhuber-rsi2016white.pdf|Learning how to Learn Learning Algorithms: Recursive Self-Improvement]]. - slides \\ ===== Evaluation: Worlds, Tasks, Environments [ 3,6 ] ===== * [[http://alumni.media.mit.edu/~kris/ftp/EGPAI_2016_paper_9.pdf|Evaluation of General-Purpose Artificial Intelligence: Why, What & How]] by J. Bieger et al. * [[http://alumni.media.mit.edu/~kris/ftp/AGIEvaluationFlexibleFramework-ThorissonEtAl2015.pdf|Towards Flexible Task-Environments For Comprehensive Evaluation of Artificial Intelligent Systems & Automatic Leaners]] by K. R. Thórisson et al. * [[http://alumni.media.mit.edu/~kris/ftp/AGI16_task_theory.pdf|Why Artificial Intelligence Needs a Task Theory — And What It Might Look Like]] by K. R. Thórisson et al. * [[http://ftp.cs.ucla.edu/pub/stat_ser/r284-reprint.pdf|BAYESIANISM AND CAUSALITY, OR, WHY I AM ONLY A HALF-BAYESIAN]] by J. Pearl * [[https://www.aaai.org/ojs/index.php/aimagazine/article/view/2748/2650|A New AI Evaluation Cosmos: Ready to Play the Game?]] by J. Hernandez-Orallo et al. * [[https://en.wikipedia.org/wiki/Hybrid_system|Hybrid systems]] on Wikipedia. * [[http://agi-conf.org/2010/wp-content/uploads/2009/06/paper_54.pdf|The Toy Box Problem]] by Johnston * [[https://chatbotsmagazine.com/how-to-win-a-turing-test-the-loebner-prize-3ac2752250f1|Loebner Prize article]] by Charlie Moloney. * [[http://alumni.media.mit.edu/~kris/ftp/EGPAI_2016_paper_8.pdf|FraMoTEC: Modular Task-Environment Construction Framework for Evaluating Adaptive Control Systems]] by Thorarensen et al. * [[http://arxiv.org/pdf/1410.6142v3.pdf|The Lovelace Test]] by M. Reidl. * [[http://kryten.mm.rpi.edu/Bringsjord_Licato_PAGI_071512.pdf | Psychometric Artificial General Intelligence: The Piaget-MacGuyver Room]] by Bringsjord, S. & Licato, J. In Theoretical Foundations of Artificial General Intelligence, edited by P. Wang and B. Goertzel (Atlantis Press). * [[http://research.microsoft.com/en-us/um/people/lamport/pubs/time-clocks.pdf|Time, Clocks, and the Ordering of Events in a Distributed System]] by L. Lamport. * [[http://cadia.ru.is/wiki/_media/public:t-720-atai:goebeletal-hybriddynamicalsystems-2009.pdf|Hybrid Dynamical Systems]] by R. Goebel et al. * [[http://www.atlantis-press.com/php/download_paper.php?id=1826 | AGI Preschool: A Framework for Evaluating Early-Stage Human-like AGIs]] by Goertzel, B. & Bugaj, S. V. Proceedings of the Second Conference on Artificial General Intelligence, Atlantis Press. * [[http://pub.ist.ac.at/~tah/Publications/the_theory_of_hybrid_automata.pdf|Theory of Hybrid Automata]] by T. A. Henzinger. * [[http://webpages.math.luc.edu/~rgoebel1/publications/conferences/GoebelHespanhaTeelCaiSanfelice04NOLCOS.pdf|HYBRID SYSTEMS: GENERALIZED SOLUTIONS AND ROBUST STABILITY]] by R. Goebel et al. \\ \\ \\ \\ =====Foundational Topics===== === Prerequisites === * [[http://www.iep.utm.edu/chineser/|Searle's Chinese Room Argument]] on the Internet Encyclopedia of Philosophy * [[https://en.wikipedia.org/wiki/Chinese_room|The Chinese Room]] on Wikipedia ===Symbols & Meaning [3,5] === * [[http://ai.stanford.edu/~nilsson/OnlinePubs-Nils/PublishedPapers/pssh.pdf|The Physical Symbol System Hypothesis: Status & Prospects]] by N. J. Nilsson. * [[http://cogprints.org/7150/1/10.1.1.83.5248.pdf|Minds, Brains & Programs]] by John Searle * [[http://consc.net/papers/subsymbolic.pdf|Subsymbolic Computation and the Chinese Room]] by D. Chalmers * [[http://arxiv.org/pdf/cs/0002009.pdf|Syntactic Autonomy - Or Why There is no Autonomy Without Symbols and how Self-Organizing Systems Might Evolve Them]] by L. M. Rocha * [[http://www.informatics.indiana.edu/rocha/publications/pattee/pattee.html|The Physics of Symbols: Bridging the Epistemic Cut]] by H. H. Pattee * [[http://www.damer.com/pub-audio/evogrid/word-versions/EndNote-Library/Damer-EndNote-Library.Data/PDF/Abel2008%20-3295737861/Abel2008%20.pdf|The 'Cybernetic Cut': Progressing from Description to Prescription in Systems Theory]] by D. L. Abel === Self-Organization & Emergence [1,2] === * [[http://web.stanford.edu/dept/HPS/WritingScience/RochaSelfOrganisation.pdf|Selected Self-Organization and the Semiotics of Evolutionary Systems]] by L. M. Rocha * [[http://people.reed.edu/~mab/publications/papers/weak-emergence.pdf|Weak Emergence]] by M. A. Bedau === (Phenomenal) Consciousness [0,2] === * [[http://organizations.utep.edu/portals/1475/nagel_bat.pdf|What's it Like to be a Bat?]] by T. Nagel * [[http://consc.net/papers/nature.pdf|Consciousness and its Place in Nature]] by D. J. Chalmers * [[https://www.youtube.com/watch?v=1d5RetvkkuQ|The Future of Consciousness]] - TEDx lecture by R. Hameroff * [[https://www.youtube.com/watch?v=GzCvlFRISIM|Consciousness is a Mathematical Pattern]] - TEDx lecture by M. Tegmark * [[https://www.youtube.com/watch?v=j_OPQgPIdKg|Consciousness and the Brain]] - TEDx lecture by J. Searle \\ \\ =====Societal Impact & Ethics [0,2] ===== * [[http://mobile.abc.net.au/news/2018-09-18/china-social-credit-a-model-citizen-in-a-digital-dictatorship/10200278?pfmredir=sm|Leave no dark corner]] by Matthew Carney. * [[https://www.oxfordmartin.ox.ac.uk/downloads/academic/The_Future_of_Employment.pdf|THE FUTURE OF EMPLOYMENT: HOW SUSCEPTIBLE ARE JOBS TO COMPUTERISATION?]] by Frey and Osborne \\ \\ ===== Additional Readings & Study Material ====== === Reinforcement Learning [ 0,2 ] === * [[https://webdocs.cs.ualberta.ca/~sutton/book/the-book.html|Reinforcement Learning: An Introduction]] by Rich Sutton and Andrew Barto (1998) is //the// introductory text on RL. * [[http://www.vetta.org/documents/Machine_Super_Intelligence.pdf|Machine Super Intelligence]] is Shane Legg's 2008 PhD thesis. While it is not on reinforcement learning, it does connect the concepts of RL to AI, what he calls "universal AI". * [[https://www.udacity.com/course/reinforcement-learning--ud600|Reinforcement Learning]] is a full Udacity course on RL from Georgia Tech. * [[https://www.youtube.com/playlist?list=PLf6J8du4ey8CL0pUxbLQpdbbtDcc2M1bI|A Short Course on Reinforcement Learning]] by Satinder Singh at MLSS'11 introduces RL and discusses some important shortcomings and proposed first steps to solving them. * [[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://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 === Deep Learning [ 0,1 ]=== * [[https://www.codementor.io/james_aka_yale/a-gentle-introduction-to-neural-networks-for-machine-learning-hkijvz7lp|A gentle introduction to neural networks]] - gives a good overview of the different approaches === Other [ 0,3 ] === * [[https://www.aaai.org/ocs/index.php/FSS/FSS15/paper/view/11702/11476| Kognit: Intelligent Cognitive Enhancement Technology by Cognitive Models and Mixed Reality for Dementia Patients]] by D. Sonntag and [[https://vimeo.com/132704158|accompanying video]] * [[http://bicasociety.org/cogarch/architectures.htm| Comparison table of cognitive architectures]], courtesy of BICA Society / Alexei Samsonovich * [[http://qz.com/627989/why-are-so-many-smart-people-such-idiots-about-philosophy/|Why are so many smart people such idiots about philosophy?]] by O. Goldhill * [[http://alumni.media.mit.edu/~kris/ftp/CognitiveMapIEEE-09.pdf|Cognitive Map Architecture: Facilitation of Human-Robot Interaction in Humanoid Robots]] by V. Ng-Thow-Hing et al. (2009). * [[http://www.aaai.org/Papers/Symposia/Fall/2004/FS-04-01/FS04-01-014.pdf | Toward a unified artificial intelligence]] by Wang, P. * [[https://www.youtube.com/watch?v=8nHVUFqI0zk|Judea Pearl lecture on Causation]] on YouTube * [[https://www.willamette.edu/~gorr/classes/ids101/links/nutshell.pdf|Creativity in a Nutshell]] by M. Boden. * Militello, L.G., Dominguez, C.O., Lintern, G. & Klein, G. (2010). **The Role of Cognitive Systems Engineering in the Systems Engineering Design Process**. In Systems Engineering, Vol 13(3), pp. 261-273. [[http://www.ppi-int.com/files/role-of-cse-in-se.pdf| PDF]] * Pan, S. J. & Yang, Q. (2011). **A survey on transfer learning**. IEEE Transactions on Knoweledge and Data Engineering, 22(10), pp. 1345–1359. [[http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.158.4126&rep=rep1&type=pdf| PDF]] * Sanz, R., Hernandez, C., Gomez, J., Bermejo-Alonso, J., Rodriguez, M., Hernando, A. & Sanchez, G. (2009). **Systems, models and self-awareness: Towards architectural models of consciousness**. International Journal Of Machine Consciousness, 1(2), pp.255–279. [[http://tierra.aslab.upm.es/documents/controlled/ASLAB-A-2009-016.pdf | PDF]] * Silver, D.L. & Poirier, R. (2007). **Requirements for Machine Lifelong Learning**. IWINAC, LNCS (4527), pp.313-319. [[http://wiki.humanobs.org/_media/public:events:agi-summerschool-2012:silverpaper_reqforml3.pdf| PDF]] * [[http://www.lehigh.edu/~mhb0/physicalemergence.pdf| PHYSICALISM, EMERGENCE AND DOWNWARD CAUSATION]] by Campbell and Bickhard * [[http://agi-school.org/2009/dr-joscha-bach-man-as-machine|Man as Machine]] - Joscha Bach's AGI intro lecture at AGI Summer School 2009 * {{:public:t-720-atai:atai-16:silver2016.pdf|Mastering the game of Go with deep neural networks and tree search}} by Silver, Huang et al. (DeepMind) * [[http://www.scottaaronson.com/papers/philos.pdf|Why Philosophers Should Care About Computational Complexity]] by S. Aaronsson * [[http://www-verimag.imag.fr/~sifakis/RecentPublications/2011/AVisionforCS.pdf|A Vision for Computer Science - the System Perspective]] by J. Sifakis \\ ===== Additional Sources ====== * [[http://www.degruyter.com/view/j/jagi| Journal of Artificial General Intelligence]] * [[http://aima.eecs.berkeley.edu/~russell/intro.html|Introduction to Artificial Intelligence - A Modern Approach]] by S. Russell & P. Norvig * [[http://philosophy.wisc.edu/forster/520/Chapter%201.pdf|Chapter 1: An Introduction to Philosophy of Science]] by Malcolm Forster \\ \\ \\ \\ //EOF//