Month: March 2019

Fathers of the Deep Learning Revolution Receive ACM A.M. Turing Award

Bengio, Hinton and LeCun Ushered in Major Breakthroughs in Artificial Intelligence New York, NY, March 27, 2019 – ACM, the Association for Computing Machinery, today named Yoshua Bengio, Geoffrey Hinton, and Yann LeCun recipients of the 2018 ACM A.M. Turing Award for conceptual and engineering breakthroughs that have made deep neural networks a critical component of computing. Bengio is Professor at the University of Montreal and Scientific Director at Mila, Quebec’s Artificial Intelligence Institute; Hinton is VP and Engineering Fellow of Google, Chief Scientific Adviser of The Vector Institute, and University Professor Emeritus at the University of Toronto; and LeCun is Professor at New York

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Call for Papers – CM-MAPS 2019

The 1st International Workshop on Conceptual Modeling for Multi-Agent Problem Solving will take place from August 10th to 12th, in combination with IJCAI 2019 in Macao, China. You can see a list of the relevant topics of the workshop below: * Conceptual artifacts to visualize and compose multi-agent problem   solvers and their requirements * Languages to specify and reason about high-level problem solving * Cooperation frameworks among multiple agents to solve a problem * Task allocation and quality and efficiency issues * Workflow driven coordination to enact and deploy multi-agent problem   solver * Formalisms to bridge conceptual and formal models

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IJCAI 2019 Workshop on Conceptual Modeling for Multi Agent Problem Solving

IJCAI 2019 Workshop on Conceptual Modeling for Multi Agent Problem Solving This workshop is one result of the Dagstuhl Seminar 18471 on Next-generation Domain-Specific Modeling: Principles and Methods https://www.dagstuhl.de/de/programm/kalender/semhp/?semnr=18471 Call for Papershttp://vienna.omilab.org/repo/files/CM-MAPS/CM-MAPS2019-CfP-v4.pdf (PDF-Download) One of the initial aspects of artificial intelligence studied was problem-solving by autonomous systems. But it was quickly realized that many problems could not be solved by a single autonomous system, and in fact, a single system may not have a complete understanding of the complete problem being solved. Hence, with this as background, the area of cooperative problem solving, distributed artificial intelligence, and multi-agent systems as

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