Language Grounding in Robots
A Reflective Architecture for Robust Language Processing and Learning
Becoming a proficient speaker of a language requires more than just learning a set of words and grammar rules, it also implies mastering the ways in which speakers of that language typically innovate: stretching the meaning of words, introducing new grammatical constructions, introducing a new category, and so on. This paper demonstrates that such meta-knowledge […]
An Experiment in Temporal Language Learning
Russian requires speakers of the language to conceptualize events using temporal language devices such as Aktionsarten and aspect, which relate to particular profiles and characteristics of events such as whether the event just started, whether it is ongoing or it is a repeated event. This chapter explores how such temporal features of events can be […]
Posture Recognition Based on Slow Feature Analysis
Basic postures such as sit, stand and lie are ubiquitous in human interaction. In order to build robots that aid and support humans in their daily life, we need to understand how posture categories can be learned and recognized. This paper presents an unsupervised learning approach to posture recognition for a biped humanoid robot. The […]
Myon, a New Humanoid
This chapter introduces the modular humanoid robot Myon, covering its mechatronical design, embedded low-level software, distributed processing architecture, and the complementary experimental environment. The Myon humanoid is the descendant of various robotic hardware platforms which have been built over the years and therefore combines the latest research results on the one hand, and the expertise […]
The Co-Evolution of Basic Spatial Terms and Categories
This chapter studies how basic spatial categories such as left-right, front-back, far-near or north-south can emerge in a population of robotic agents in co-evolution with terms that express these categories. It introduces various language strategies and tests them first in reconstructions of German spatial terms, then in acquisition experiments to demonstrate the adequacy of the […]
Emergent Mirror Systems for Body Language
This chapter investigates how a vocabulary for talking about body actions can emerge in a population of grounded autonomous agents instantiated as humanoid robots. The agents play a Posture Game in which the speaker asks the hearer to take on a certain posture. The speaker either signals success if the hearer indeed performs an action […]
A Language Strategy for Aspect: Encoding Aktionsarten through Morphology
This chapter explores a possible language strategy for verbalizing aspect: the encoding of Aktionsarten by means of morphological markers. Russian tense-aspect system is used as a model. We first operationalize this system and reconstruct the learning operators needed for acquiring it. Then we perform a first language formation experiment in which a novel system of […]
Self-Assessing Agents for Explaining Language Change: A Case Study in German
Language change is increasingly recognized as one of the most crucial sources of evidence for understanding human cognition. Unfortunately, despite sophisticated methods for documenting which changes have taken place, the question of why languages evolve over time remains open for speculation. This paper presents a novel research method that addresses this issue by combining agent-based […]
Multilevel Alignment Maintains Language Systematicity
The question how a shared vocabulary can arise in a multi-agent population despite the fact that each agent autonomously invents and acquires words has been solved. The solution is based on alignment: Agents score all associations between words and meanings in their lexicons and update these preference scores based on communicative success. A positive feedback […]