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Neural-Symbolic Cognitive Agents: Architecture and Theory.

, , , and . ICCSW, volume DTR11-9 of Department of Computing Technical Report, page 10-16. Imperial College London, (2011)

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Learning to adapt requirements specifications of evolving systems., , , and . ICSE, page 856-859. ACM, (2011)Estimating complex networks centrality via neural networks and machine learning., and . IJCNN, page 1-8. IEEE, (2015)On approximating networks centrality measures via neural learning algorithms., and . IJCNN, page 551-557. IEEE, (2016)Distributed problem solving by memetic networks: extended abstract., and . GECCO, page 599-600. ACM, (2008)Reasoning about Time and Knowledge in Neural Symbolic Learning Systems., and . NIPS, page 921-928. MIT Press, (2003)Neural-Symbolic Relational Reasoning on Graph Models: Effective Link Inference and Computation from Knowledge Bases., , , , and . ICANN (1), volume 12396 of Lecture Notes in Computer Science, page 647-659. Springer, (2020)Towards Reasoning about the Past in Neural-symbolic Systems., , and . NeSy, volume 230 of CEUR Workshop Proceedings, CEUR-WS.org, (2007)Measuring Ethics in AI with AI: A Methodology and Dataset Construction., , and . BRACIS (1), volume 13653 of Lecture Notes in Computer Science, page 370-384. Springer, (2022)Collaboration in Social Problem-Solving: When Diversity Trumps Network Efficiency., , , and . AAAI, page 1277-1283. AAAI Press, (2015)Combining Human Reasoning and Machine Computation: Towards a Memetic Network Solution to Satisfiability., , and . AAAI, page 1929-1930. AAAI Press, (2010)