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We have sorted the reading material for the Summer School in a way intended to 
help prioritizing which papers to read first. Even though the second-level of 
importance is called "Recommended Readings" these are essentially just as 
important as those in the "Required Readings" list, and we strongly advice that 
as many of these papers be read before the Summer School starts. In case some 
of you are behind on readings, we have also listed for each presentation which 
papers are most important (see link to Lecturers below).

Invited Lecturers


Required Readings

Anderson, J. R.; Bothell, D.; Byrne, M.D.; Douglass, S.; Lebiere, C. & Qin, Y. (2004). (ACT-R) An Integrated Theory of the Mind. Psychological Review, Vol 111(4), pp. 1036-1060 PDF

Björnsson, Y. & Finnsson, H. (2009). CadiaPlayer: A Simulation-Based General Game Player. IEEE Transactions on Computational Intelligence and AI in Games 1(1), pp. 4–15. PDF

Bringsjord, S. (2008) Declarative/Logic-Based Computational Cognitive Modeling. In R. Sun (ed. ), The Cambridge Handbook of Computational Psychology (Cambridge, UK: Cambridge University Press), pp. 127–169. PDF

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. PDF

Garlan, D., R. Allen and J. Ockerbloom (1995). Architectural Mismatch or Why it’s hard to build systems out of existing parts. Proceedings of the Seventeenth International Con- ference on Software Engineering, Seattle WA. PDF

Goertzel, B. (2009) Opencog prime: A cognitive synergy based architecture for embodied artificial general intelligence. In Proceedings of ICCI-09, Hong Kong. PDF

Heylighen, F. & C. Joslyn (2001). Cybernetics and Second-Order Cybernetics. In R.A. Meyers (ed.), Encyclopedia of Physical Science & Technology (3rd ed.), Academic Press, New York. PDF

Laird, J.E. (2008). Extending the Soar Cognitive Architecture. In Proc. of the 2008 conference on Artificial General Intelligence. Pei Wang, Ben Goertzel, and Stan Franklin (Eds.). IOS Press, Amsterdam, The Netherlands, The Netherlands, pp. 224-235. PDF

Laird, J.E. & Wray, R.E. (2010). Cognitive Architecture Requirements for Achieving AGI. Proceedings of the Third Conference on Artificial General Intelligence, AGI 2010, Lugano, Switzerland, March 5-8. PDF

Langley, P., Laird, J.E., Rogers, S. (2009) Cognitive architectures: Research issues and challenges. Cognitive Systems Research Vol 10(2), pp. 141-160. PDF

Sanz, R.; López, I. & Hernández, C. (2007). Self-awareness in Real-time Cognitive Control Architectures. AI and Consciousness: Theoretical Foundations and Current Approaches. AAAI Fall Symposium 2007. Washington, DC. 8-11 November. PDF

Sanz, R.; López, I.; Rodríguez, M. & Hernández, C. (2007). Principles for Consciousness in Integrated Cognitive Control. Neural Networks, Vol 20/9, pp. 938-946. PDF

Schwering, A.; Krumnack, U.; Kühnberger, K.-U. & Gust, H. (2009). Syntactic Principles of Heuristic-Driven Theory Projection. Cognitive Systems Research 10(3):251-269 PDF

Silver, D.L.; Poirier, R.; Currie, D. (2008). Inductive transfer with context-sensitive neural networks. Machine Learning 73(3): 313-336. PDF

Sloman, A. (2011). Requirements for a Fully-deliberative Architecture. Weblink

Sloman, A. (2000). Architectural Requirements for Human-like Agents Both Natural and Artificial. In K. Dautenhahn (ed.), Human Cognition and Social Agent Technology, in the Series “Advances in Consciousness Research”, John Benjamins Publishing. PDF

Thórisson, K. R. (2009). From Constructionist to Constructivist A.I. Keynote@AAAI Fall Symposium Series: Biologically Inspired Cognitive Architectures, Washington D.C., Nov. 5-7, 175-183. AAAI Tech Report FS-09-01, AAAI press, Menlo Park, CA. PDF

Thórisson, K. R. & H. P. Helgason (2012). Cognitive Architectures and Autonomy: A Comparative Review. Journal of Artificial General Intelligence, 3(2), 1-30. on JAGI website PDF

Wang, P. (2007). From NARS to a thinking machine. Advances in artificial general intelligence: concepts, architectures and algorithms. PDF



Architecture / Methodology

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 | PDF

Bringsjord, S. & Licato, J. (forthcoming) Psychometric Artificial General Intelligence: The Piaget-MacGuyver Room. In Theoretical Foundations of Artificial General Intelligence, edited by P. Wang and B. Goertzel (Atlantis Press). PDF

Goertzel, Ben (2010). What Must a World Be Like That a Human-Like Intelligence May Develop In It. PDF

Goertzel, B. & Bugaj, S. V. AGI Preschool: A Framework for Evaluating Early-Stage Human-like AGIs. Proceedings of the Second Conference on Artificial General Intelligence, Atlantis Press. 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 PDF

Sanz, R.; López, I. & Hernández, C. (2007). Self-awareness in Real-time Cognitive Control Architectures. AI and Consciousness: Theoretical Foundations and Current Approaches. AAAI Fall Symposium 2007. Washington, DC. 8-11 November. 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 PDF

Thórisson, K. R. & Nivel, E. (2009). Achieving Artificial General Intelligence Through Peewee Granularity. Proc. of the Second Conference on Artificial General Intelligence, 222-223. Arlington, VA, USA, March 6-9. PDF

Thórisson, K. R. (1999). A Mind Model for Multimodal Communicative Creatures and Humanoids. International Journal of Applied Artificial Intelligence, 13(4-5): 449-486. PDF

Self-Programming

Nivel, E. & K. R. Thórisson (2009). Self-Programming: Operationalizing Autonomy. Proc. of the Second Conference on Artificial General Intelligence, 150-155. Arlington, VA, USA, March 6-9. PDF

Wang, P. (2011). Behavioral Self-Programming by Reasoning. Workshop on Self-Programming, AGI Conference 2011, PDF

Reasoning & Logic

Guhe, M.; Pease, A.; Smaill, A.; Martínez, M.; Schmidt, M.; Gust, H.; Kühnberger, K.-U. & Krumnack, U. (2011): A Computational Account of Conceptual Blending in Basic Mathematics, Cognitive Systems Research 12(3-4):249-265 PDF

Wang, P. (2004). Toward a unified artificial intelligence. AAAI Fall Symposium on Achieving Human-Level Intelligence through Integrated Research and Systems. pp. 83-90. PDF

Learning

Dindo, H.; Chella, A.; La Tona, G.; Vitali, M.; Nivel, E. & Thórisson, K. R. (2011). Learning Problem Solving Skills from Demonstration: An Architectural Approach. Proceedings of Artificial General Intelligence 2011. PDF

Goertzel, B., Pitt, J., Wigmore, J., Geisweiller, N., Cai, Z., Lian, R., Huang, D., & Yu, G. (2011). Cognitive Synergy between Procedural and Declarative Learning in the Control of Animated and Robotic Agents Using the OpenCogPrime AGI Architecture. Proceedings of AAAI-11 , PDF

Ramamurthy, U.; Baars, B.J.; D'Mello, S. K. & Franklin, S. (2006). LIDA: A Working Model of Cognition. PDF

Silver, D.L. (2011). Machine Lifelong Learning: Challenges and Benefits for Artificial General Intelligence. AGI 2011: 370-375. PDF

Game playing

Clune, J. (2007). Heuristic Evaluation Functions for General Game Playing. Proceedings of the 22nd AAAI Conference on Artificial Intelligence (AAAI-07), pp. 1134—1139. PDF

Finnsson, H. & Björnsson, Y. (2010). Learning Simulation Control in General Game-Playing Agents. In The Twenty-Fourth AAAI Conference on Artificial Intelligence, pp. 954–959. PDF

Genesereth, M.R.; Love, N. & Pell, B. (2005). General Game Playing: Overview of the AAAI Competition. AI Magazine 26(2), pp.62-72. PDF

Sub-symbolic Approaches

Goertzel, B. (2011). A Novel Strategy for Hybridizing Subsymbolic and Symbolic Learning and Representation. Proceedings of AAAI Symposium on Cognitive Systems, Arlington VA. PDF

Probabilistic Approaches

Griffiths, T. L.; Kemp, C. & Tenenbaum, J. B. (2008). Bayesian models of cognition. Cambridge Handbook of Computational Cognitive Modeling. Cambridge University Press PDF

Hybrid systems

Gust, H.; Kühnberger, K.-U. & Schmid, U. (2006). Metaphors and Heuristic-Driven Theory Projection (HDTP), Theoretical Computer Science, 354:98-117 PDF

Supporting Material

Adams, S. S., Arel, I., Bach, J., Coop, R., Furlan, R., et al. (2012). Mapping the Landscape of Human-Level Artificial General Intelligence. In AI Magazine, Vol 33(1), pp. 25-41. PDF

Arel, I.; Rose, D. & Karnowski, T. (2009). A deep learning architecture comprising homogeneous cortical circuits for scalable spatiotemporal pattern inference. NIPS 2009 Workshop on Deep Learning for Speech Recognition and Related Applications, PDF

Goertzel, B. (2012). Perception Processing for General Intelligence, Part I: Representationally Transparent Deep Learning. PDF

Goertzel, B. (2012). Perception Processing for General Intelligence, Part II: Bridging the Symbolic/Subsymbolic Gap. PDF

Goertzel, B.; Pitt, J.; Cai, Z.; Wigmore, J.; Huang, D.; Geisweiller, N.; Lian, R. & Yu, G. (2011). Integrative General Intelligence in a Minecraft-Type Environment. Proceedings of BICA-2011, Arlington VA. PDF

Hawkins, J. & Blakeslee, S. On Intelligence. LINK

Hernandez, C. & Sanz, R. (2012). Three patterns for autonomous systems. Technical Note ASLAB-A-2012- 007, Autonomous Systems Laboratory. Universidad Politecnica de Madrid. PDF

IEEE Standards Association.(1998). IEEE Recommended Practice for Software Requirements Specifications. PDF

Karnowski, T; Arel, I. & Rose, D. (2010). Deep Spatiotemporal Feature Learning with Application to Image Classification. ICMLA, pp. 883-888, PDF

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. PDF

Nuseibeh, B. & Easterbrook, S. (2000). Requirements Engineering: A Roadmap. Published in Pro ICSE '00 Proceedings of the Conference on the Future of Software Engineering, pp. 35-46. PDF

Pan, S. J. & Yang, Q. (2011). A survey on transfer learning. IEEE Transactions on Knoweledge and Data Engineering, 22(10), pp. 1345–1359. 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. PDF

Schiffel, S. & Thielscher, M. (2007). Fluxplayer: A Successful General Game Player. Proceedings of the 22nd AAAI Conference on Artificial Intelligence (AAAI-07), pp. 1191—1196. PDF

Silver, D.L. & Poirier, R. (2007). Requirements for Machine Lifelong Learning. IWINAC, LNCS (4527), pp.313-319. PDF

Thielscher, M. (2011). General Game Playing in AI Research and Education. Proceedings of the German Annual Conference on Artificial Intelligence (KI), 2011, pp. 26—37. PDF

Wray, R. et. al. Towards a Complete, Multi-level Cognitive Architecture. PDF

public/events/agi-summerschool-2012/readings.txt · Last modified: 2012/09/03 10:15 by thorisson