This chapter shows a concrete example of a language game experiment for studying the cultural
evolution of one of the most basic functions of language, namely to draw attention to an
object in the context by naming a characteristic feature of the
object. If the object is a specific recognizable individual, then the name is called a proper name,
and this is the case that is studied in this chapter. We investigate a concrete operational language strategy,
with a conceptual as well a linguistic component, and show that a population of
agents endowed with this strategy is able to self-organize a vocabulary of grounded proper names from scratch.
The example provides a clear example of the role of alignment in stimulating self-organization and how
expressive adequacy, cognitive effort, learnability, and social conformity act as selectionist forces,
driving the population towards an effective language system.
2024. Emergent Communication in Agents Generating Messages Using Different Pretrained Deep Generative Models. Transactions of the Japanese Society for Artificial Intelligence 39:2 ► pp. D-N71_1 ff.
2024. 2024 IEEE International Conference on Development and Learning (ICDL), ► pp. 1 ff.
Kondylidis, Nikolaos
2022. Using Referential Language Games for Task-oriented Ontology Alignment. In The Semantic Web: ESWC 2022 Satellite Events [Lecture Notes in Computer Science, 13384], ► pp. 252 ff.
Kouwenhoven, Tom, Tessa Verhoef, Roy de Kleijn & Stephan Raaijmakers
2022. Emerging Grounded Shared Vocabularies Between Human and Machine, Inspired by Human Language Evolution. Frontiers in Artificial Intelligence 5
Soni, Aradhana, Kalyan S. Perumalla & Xueping Li
2022. 2022 Winter Simulation Conference (WSC), ► pp. 298 ff.
Cambier, Nicolas, Roman Miletitch, Vincent Frémont, Marco Dorigo, Eliseo Ferrante & Vito Trianni
2020. Language Evolution in Swarm Robotics: A Perspective. Frontiers in Robotics and AI 7
2020. A Cross-Situational Learning Based Framework for Grounding of Synonyms in Human-Robot Interactions. In Robot 2019: Fourth Iberian Robotics Conference [Advances in Intelligent Systems and Computing, 1093], ► pp. 225 ff.
Roesler, Oliver
2022. Combining Unsupervised and Supervised Learning for Sample Efficient Continuous Language Grounding. Frontiers in Robotics and AI 9
Chen, Guanrong & Yang Lou
2019. Introduction. In Naming Game [Emergence, Complexity and Computation, 34], ► pp. 1 ff.
Roesler, Oliver & Ann Nowé
2019. Action learning and grounding in simulated human–robot interactions. The Knowledge Engineering Review 34
de Vladar, Harold. P.
2018. Proceedings of the Genetic and Evolutionary Computation Conference Companion, ► pp. 1307 ff.
SEHYR, ZED SEVCIKOVA, BRENDA NICODEMUS, JENNIFER PETRICH & KAREN EMMOREY
2018. Referring strategies in American Sign Language and English (with co-speech gesture): The role of modality in referring to non-nameable objects. Applied Psycholinguistics 39:5 ► pp. 961 ff.
Spike, Matthew, Kevin Stadler, Simon Kirby & Kenny Smith
2017. Minimal Requirements for the Emergence of Learned Signaling. Cognitive Science 41:3 ► pp. 623 ff.
Rasheed, Nadia & Shamsudin H. M. Amin
2016. Developmental and Evolutionary Lexicon Acquisition in Cognitive Agents/Robots with Grounding Principle: A Short Review. Computational Intelligence and Neuroscience 2016 ► pp. 1 ff.
2015. Discriminating Unknown Objects from Known Objects Using Image and Speech Information. IEICE Transactions on Information and Systems E98.D:3 ► pp. 704 ff.
Gao, Yuan, Guanrong Chen & Rosa H. M. Chan
2014. Naming Game on Networks: Let Everyone be Both Speaker and Hearer. Scientific Reports 4:1
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