How Should Intelligence Be Abstracted in AI Research: MDPs, Symbolic Representations, Artificial Neural Networks, or ? Papers from the AAAI Symposium
Sebastian Risi, Joel Lehman, Jeff Clune, Cochairs
November 15–17, 2013, Arlington, Virginia
Technical Report FS-13-02
Contents
Organizing Committee
Sebastian Risi, Joel Lehman, Jeff Clune
Preface
Sebastian Risi, Joel Lehman, Jeff Clune
How Can the Blind Men See the Elephant?
Bonny Banerjee
Systematic Variation in Cytoarchitectural Landscapes in the Isocortex of Primates and Rodents
Christine Charvet, Diarmuid Cahalane, Barbara Finlay
Models of Brains: What Should We Borrow From Biology?
Oliver J. Coleman, Alan D. Blair
Distributional Relational Networks
André Freitas, João C. P. da Silva, Se&acaute;n O’Riain, Edward Curry
Combining a POMDP Abstraction with Replanning to Solve Complex, Position-Dependent Sensing Tasks
Devin Grady, Mark Moll, Lydia E. Kavraki
Operational Representation — A Unifying Representation for Activity Learning and Problem Solving
Seng-Beng Ho
Guiding Evolutionary Learning by Searching for Regularities in Behavioral Trajectories: A Case for Representation Agnosticism
Krzysztof Krawiec, Jerry Swan
Reflections on Abstractions for General Artificial Intelligence
John Edwin Laird
Quantitative Symbolic Process Models: How a Fair Fraction of Intelligence Could Be Abstracted in AI Research
Eric Mjolsness
Artificial Life and Machine Consciousness
Andrew L. Nelson
How to Abstract Intelligence? (If Verification Is in Order)
Shashank Pathak, Luca Pulina, Giorgio Metta, Armando Tacchella
The Case for Evolution in Engineering Brains
Kenneth O. Stanley
Predicting Situated Behaviour Using Sequences of Abstract Spatial Relations
Jay Young, Nick Hawes
Integrating Declarative Programming and Probabilistic Planning for Robots
Shiqi Zhang, Mohan Sridharan
Soft Rule Ensembles for Supervised Learning
Deniz Akdemir, Nicolas Heslot, Jean-Luc Jannink
An Ecological Development Abstraction for Artificial Intelligence
Samuel H. Kenyon
Exploring Biological Intelligence through Artificial Intelligence and Radical Reimplementation
Joel Lehman, Kenneth O. Stanley
A Compiler for CPPNs: Transforming Phenotypic Descriptions Into Genotypic Representations
Sebastian Risi
Sports Video Classification from Multimodal Information Using Deep Neural Networks
Devendra Singh Sachan, Umesh Tekwani, Amit Sethi
Carving Out Evolutionary Paths Towards Greater Complexity
Gene Sher
Evolutionary Scheduler for Content Pre-Fetching in Mobile Networks
Omar K. Shoukry, Magda B. Fayek
Reasoning with Uncertainties Over Existence of Objects
Vien Anh Ngo, Marc Toussaint
An Introduction to the Cognitive Calculus: A Calculus of the Human Mind
Christian C. Wagner, James G. Schiiller
Nothing Is Absolute
Ke Wang
A Myriad of Automation Serving a Unified Reflective Safe/Moral Will
Mark R. Waser
Natural Information and Computation: A Proposal Based on Interaction and Decision Making
Rafael Silveira Xavier, Leandro Nunes de Castro