Evolving grounded communication for robots.

By Luc Steels. Trends in Cognitive Sciences, 2003

444 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Cultural Studies, Social Psychology

View Paper: https://www.semanticscholar.org/paper/1c07bba0dfecb05884b4dfcd46f409451617e88f

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Citations in the corpus

Discovering communication (2006, background): “In the last 10 years, a growing number of researchers have taken up the interdisciplinary challenge to understand language formation and evolution through computational and robotic models (see Cangelosi and Parisi 2002, Kirby 2002, Steels 2003 for general overviews of the ﬁeld).”
A review of verbal and non-verbal human-robot interactive communication (2014, background): “Highly relevant work includes: [70] and also Steels [71], [72], [73], and also [74] from a child lexical perspective.”
Agent-Based Models of Strategies for the Emergence and Evolution of Grammatical Agreement (2013, unknown): “feature analysis and categorisation, as in [21,22].”
Pommerman: A Multi-Agent Playground (2018, background): “…2016; Resnick et al. 2018d; Evtimova et al. 2017; Foerster et al. 2017; Lewis et al. 2017; Mordatch and Abbeel 2017; Lazaridou et al. 2018) with established prior work as well (Steels 1999; Steels 2003; Levy and Kirby 2006; Fehervari and Elmenreich 2010), while the latter has been underexplored.”
Words as alleles: connecting language evolution with Bayesian learners to models of genetic drift (2010, background): “This process of iterated learning provides a simple way to examine the consequences of this form of cultural transmission in isolation from other factors that might be involved in language evolution, such as the pressure to create a shared communication system (Komarova & Nowak 2001, 2003; Steels 20”
On the Impact of Robotics in Behavioral and Cognitive Sciences: From Insect Navigation to Human Cognitive Development (2010, unknown): “For example, the Talking Head Experiments [69], [140], [141] has shown how a community of robots could build a shared lexicon only through local social interactions.”
Embodied Artificial Intelligence: Trends and Challenges (2003, background): “An excellent example of this type of research that tries to combine population thinking or multi-agent systems with higher-level processes such as language is the “Talking Heads” experiment by Luc Steels (e.g. Steels, 2001, 2003).”
The symbol grounding problem has been solved, so what’s next? (2008, background): “The past decade I have been working with a team of a dozen graduate students at the university of Brussels (VUB AI Lab) and the Sony Computer Science Lab in Paris on various experiments in language emergence (Steels,2003).”
Computational modeling of phonetic and lexical learning in early language acquisition: Existing models and future directions (2012, background): “However, the advances in technology have enabled study of language learning cognitive systems by building autonomous robots capable of sensing and acting in the real world environment (e.g., Steels and Kaplan, 2000; Steels, 2003; Roy, 2003).”
The challenges of joint attention (2006, background): “Most works implement a set of perceptual primitives capable of extracting relevant features in action sequences (e.g.(Roy and Pentland, 2002; Siskind, 2001; Dominey, 2003; Steels, 2003 )).”
Iterated learning and the evolution of language. (2014, unknown): “Following Hurford’s lead, the earliest work in this area sought to explain the role of interaction and negotiation [10 , 11] or biases of learners [12,13] in shaping communication systems, focusing in particular on the conditions under which communicatively optimal, socially learnt communication sys”