A Survey of Artificial Cognitive Systems: Implications for the Autonomous Development of Mental Capabilities in Computational Agents
By David Vernon, Giorgio Metta, Giulio Sandini. IEEE Transactions on Evolutionary Computation, 2007
472 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computational Theory and Mathematics
View Paper: https://www.semanticscholar.org/paper/da67375c8b6a250fbd5482bfbfce14f4eb7e506c
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Manuel Lopes
- Luis Montesano
- John K. Tsotsos
- José Santos-Victor
- Iuliia Kotseruba
- Alexandre Bernardino
- Lorenzo Natale
- Giulio Sandini
In Computational Theory and Mathematics
- John K. Tsotsos
- Iuliia Kotseruba
- Manuel Lopes
- Giulio Sandini
- Olaf Sporns
- Giorgio Metta
- Bernhard Sendhoff
- Péter Zoltán Baranyi
Citations in the corpus
- Definition and synergies of cognitive infocommunications (2012, background): “Parallel to these developments, with the enormous growth in scope and generality of cognitive sciences in the past few decades, the new fields of cognitive media [31, 23], cognitive informatics [49, 48, 44] and cognitive communications [34, 16] are gradually emerging.”
- A Multi-Facet Survey on Memetic Computation (2011, unknown): “From a software perspective, a memetic automaton is a software agent capable of autonomic behavior during problemsolving [162], [163].”
- The iCub humanoid robot: An open-systems platform for research in cognitive development (2010, background): “…of cognitive systems could not progress without a certain number of ingredients: the development of a sound formal understanding of cognition (Vernon, Metta, & Sandini, 2007), the study of natural cognition and, particularly important, the study of the development of cognition (Sandini,…”
- 40 years of cognitive architectures: core cognitive abilities and practical applications (2018, methodology): “2008), iCub (Vernon et al. 2010) and MACSi (Ivaldi et al.”
- Creating Brain-Like Intelligence (2009, background): “Indeed their last criterion suggests to use experimental data from neuroscience to measure performance; we will come back to this point again in Section 7. The review article by Vernon et al. [ 14 ] nicely summarizes the trend that the two traditionally opposing camps of relying on physical symbol s”