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Miquel Cornudella

Assistant Researcher - PhD Student

language

2016

The Role of Intrinsic Motivation in Artificial Language Emergence: a Case Study on Colour

Topics:
Language
Authors
Miquel Cornudella , Poibeau Thierry , Remi van Trijp |

Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, The COLING 2016 Organizing Committee, Osaka, 2016. pp.1646--1656.

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Abstract

Human languages have multiple strategies that allow us to discriminate objects in a vast variety of contexts. Colours have been extensively studied from this point of view. In particular, previous research in artificial language evolution has shown how artificial languages may emerge based on specific strategies to distinguish colours. Still, it has not been shown how several strategies of diverse complexity can be autonomously managed by artificial agents . We propose an intrinsic motivation system that allows agents in a population to create a shared artificial language and progressively increase its expressive power. Our results show that with such a system agents successfully regulate their language development, which indicates a relation between population size and consistency in the emergent communicative systems.

2015

How Intrinsic Motivation can Speed Up Language Emergence

Topics:
Language
Authors
Miquel Cornudella , Paul Van Eecke , Remi van Trijp |

Proceedings of the European Conference on Artificial Life 2015, edited by:Andrews, Paul and Caves, Leo and Doursat, Ren'{e} and Hickinbotham, Simon and Polack, Fiona and Stepney, Susan and Taylor, Tim, MIT Press, Cambridge MA, 2015. pp.571--578.

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Abstract

Natural languages enable humans to engage in highly complex social and conversational interactions with each other. Alife approaches to the origins and emergence of language typically manage this complexity by carefully staging the learning paths that embodied artificial agents need to follow in order to bootstrap their own communication system from scratch. This paper investigates how these scaffolds introduced by the experimenter can be removed by allowing agents to autonomously set their own challenges when they are driven by intrinsic motivation and have the capacity to self-assess their own skills at achieving their communicative goals. The results suggest that intrinsic motivation not only allows agents to spontaneously develop their own learning paths, but also that they are able to make faster transitions from one learning phase to the next.