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  1. The Surprising Creativity of Digital Evolution: A Collection of Anecdotes From the Evolutionary Computation and Artificial Life Research Communities.Joel Lehman, Jeff Clune, Dusan Misevic, Christoph Adami, Julie Beaulieu, Peter Bentley, Bernard J., Belson Samuel, Bryson Guillaume, M. David, Nick Cheney, Antoine Cully, Stephane Donciuex, Fred Dyer, Ellefsen C., Feldt Kai Olav, Fischer Robert, Forrest Stephan, Frénoy Stephanie, Gagneé Antoine, Goff Christian, Grabowski Leni Le, M. Laura, Babak Hodjat, Laurent Keller, Carole Knibbe, Peter Krcah, Richard Lenski, Lipson E., MacCurdy Hod, Maestre Robert, Miikkulainen Carlos, Mitri Risto, Moriarty Sara, E. David, Jean-Baptiste Mouret, Anh Nguyen, Charles Ofria, Marc Parizeau, David Parsons, Robert Pennock, Punch T., F. William, Thomas Ray, Schoenauer S., Shulte Marc, Sims Eric, Stanley Karl, O. Kenneth, Fran\C. Cois Taddei, Danesh Tarapore, Simon Thibault, Westley Weimer, Richard Watson & Jason Yosinksi - 2018 - CoRR.
    Biological evolution provides a creative fount of complex and subtle adaptations, often surprising the scientists who discover them. However, because evolution is an algorithmic process that transcends the substrate in which it occurs, evolution’s creativity is not limited to nature. Indeed, many researchers in the field of digital evolution have observed their evolving algorithms and organisms subverting their intentions, exposing unrecognized bugs in their code, producing unexpected adaptations, or exhibiting outcomes uncannily convergent with ones in nature. Such stories routinely reveal (...)
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  • Artificial Intelligence, Values, and Alignment.Iason Gabriel - 2020 - Minds and Machines 30 (3):411-437.
    This paper looks at philosophical questions that arise in the context of AI alignment. It defends three propositions. First, normative and technical aspects of the AI alignment problem are interrelated, creating space for productive engagement between people working in both domains. Second, it is important to be clear about the goal of alignment. There are significant differences between AI that aligns with instructions, intentions, revealed preferences, ideal preferences, interests and values. A principle-based approach to AI alignment, which combines these elements (...)
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  • Machines learning values.Steve Petersen - 2020 - In S. Matthew Liao (ed.), Ethics of Artificial Intelligence. Oxford University Press.
    Whether it would take one decade or several centuries, many agree that it is possible to create a *superintelligence*---an artificial intelligence with a godlike ability to achieve its goals. And many who have reflected carefully on this fact agree that our best hope for a "friendly" superintelligence is to design it to *learn* values like ours, since our values are too complex to program or hardwire explicitly. But the value learning approach to AI safety faces three particularly philosophical puzzles: first, (...)
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  • From Bacteria to Bach and Back: The Evolution of Minds.Daniel C. Dennett - unknown
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  • Causality: Models, Reasoning and Inference.Judea Pearl - 2000 - Tijdschrift Voor Filosofie 64 (1):201-202.
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  • Superintelligence: paths, dangers, strategies.Nick Bostrom (ed.) - 2003 - Oxford University Press.
    The human brain has some capabilities that the brains of other animals lack. It is to these distinctive capabilities that our species owes its dominant position. Other animals have stronger muscles or sharper claws, but we have cleverer brains. If machine brains one day come to surpass human brains in general intelligence, then this new superintelligence could become very powerful. As the fate of the gorillas now depends more on us humans than on the gorillas themselves, so the fate of (...)
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  • Planning and acting in partially observable stochastic domains.Leslie Pack Kaelbling, Michael L. Littman & Anthony R. Cassandra - 1998 - Artificial Intelligence 101 (1-2):99-134.
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