activity
20102022
most citedEnvironmental drivers of systematicity and generalization in a situated agent

53 citations · 156 across the 12 of their papers we have counts for

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5 papers · 1 filter

cs.AI2021

Formalising Concepts as Grounded Abstractions

Stephen Clark, Alexander Lerchner, Tamara von Glehn +4

The notion of concept has been studied for centuries, by philosophers, linguists, cognitive scientists, and researchers in artificial intelligence (Margolis & Laurence, 1999). Ther…

cs.AI20205 cited

Probing Emergent Semantics in Predictive Agents via Question Answering

Abhishek Das, Federico Carnevale, Hamza Merzic +8

Recent work has shown how predictive modeling can endow agents with rich knowledge of their surroundings, improving their ability to act in complex environments. We propose questio…

cs.AI201953 cited

Environmental drivers of systematicity and generalization in a situated agent

Felix Hill, Andrew Lampinen, Rosalia Schneider +4

The question of whether deep neural networks are good at generalising beyond their immediate training experience is of critical importance for learning-based approaches to AI. Here…

cs.AI2018

Emergence of Linguistic Communication from Referential Games with Symbolic and Pixel Input

Angeliki Lazaridou, Karl Moritz Hermann, Karl Tuyls +1

The ability of algorithms to evolve or learn (compositional) communication protocols has traditionally been studied in the language evolution literature through the use of emergent…

cs.AI2018

Emergent Communication through Negotiation

Kris Cao, Angeliki Lazaridou, Marc Lanctot +3

Multi-agent reinforcement learning offers a way to study how communication could emerge in communities of agents needing to solve specific problems. In this paper, we study the eme…