@COMMENT This file was generated by bib2html.pl version 0.94 @COMMENT written by Patrick Riley @COMMENT This file came from Gal A. Kaminka's publication pages at @COMMENT http://www.cs.biu.ac.il/~galk/publications/ @InProceedings{aamas13challenge, author = {Gal A. Kaminka}, title = {Curing Robot Autism: A Challenge}, booktitle = AAMAS-13, OPTcrossref = {}, OPTkey = {}, OPTpages = {}, year = {2013}, OPTeditor = {}, OPTvolume = {}, OPTnumber = {}, OPTseries = {}, OPTaddress = {}, OPTmonth = {}, OPTorganization = {}, OPTpublisher = {}, OPTannote = {}, OPTnote = {}, OPTurl = {}, OPTurldate = {}, OPTlastchecked = {}, OPTdoi = {}, OPTisbn = {}, OPTissn = {}, OPTlocalfile = {}, abstract = { Almost all robots are autistic; very few humans are. Out of the box, robots generally do not behave correctly in social settings (involving humans, or other agents). Most researchers treat this challenge \textit{behaviorally}, by superficially tacking task- and domain- specific social behavior onto functioning individual robots. These rules are built once, and applied once. In contrast, I posit that we can build better socially-capable robots by relying on general social intelligence building blocks, built into the brains of robots, rather than grafted on per mission: \textit{built once, applied everywhere}. I challenge the autonomous agents community to synthesize the computational building blocks underlying social intelligence, and to apply them in concrete robot and agent systems. I argue that our field is in a unique position to do this, in that our community intersects with computer science, behavioral and social sciences, robotics, and neuro-science. Thus we can bring to bear a breadth of knowledge and understanding which cannot be matched in other related fields. To lend credibility for our ability to carry out this challenge, I will demonstrate that we have carried out similar tasks in the past (though at a smaller scale). I conclude with a sample of some open questions for research, raised by this challenge. }, wwwnote = {{\bf Winner: Best challenge paper award.}}, OPTkeywords = {}, }