Recent advances in deep learning based dialogue systems: A systematic survey
Dialogue systems are a popular natural language processing (NLP) task as it is promising in
real-life applications. It is also a complicated task since many NLP tasks deserving study are …
real-life applications. It is also a complicated task since many NLP tasks deserving study are …
Emergent multi-agent communication in the deep learning era
The ability to cooperate through language is a defining feature of humans. As the
perceptual, motory and planning capabilities of deep artificial networks increase …
perceptual, motory and planning capabilities of deep artificial networks increase …
Mate: Benchmarking multi-agent reinforcement learning in distributed target coverage control
Abstract We introduce the Multi-Agent Tracking Environment (MATE), a novel multi-agent
environment simulates the target coverage control problems in the real world. MATE hosts …
environment simulates the target coverage control problems in the real world. MATE hosts …
Dynamic population-based meta-learning for multi-agent communication with natural language
In this work, our goal is to train agents that can coordinate with seen, unseen as well as
human partners in a multi-agent communication environment involving natural language …
human partners in a multi-agent communication environment involving natural language …
Metropolis-Hastings algorithm in joint-attention naming game: Experimental semiotics study
We explore the emergence of symbols during interactions between individuals through an
experimental semiotic study. Previous studies have investigated how humans organize …
experimental semiotic study. Previous studies have investigated how humans organize …
Emergent communication under varying sizes and connectivities
Recent advances in deep neural networks allowed artificial agents to derive their own
emergent languages that promote interaction, coordination, and collaboration within a …
emergent languages that promote interaction, coordination, and collaboration within a …
The emergence of the shape bias results from communicative efficiency
By the age of two, children tend to assume that new word categories are based on objects'
shape, rather than their color or texture; this assumption is called the shape bias. They are …
shape, rather than their color or texture; this assumption is called the shape bias. They are …
Toward More Human-Like AI Communication: A Review of Emergent Communication Research
N Brandizzi - IEEE Access, 2023 - ieeexplore.ieee.org
In the recent shift towards human-centric AI, the need for machines to accurately use natural
language has become increasingly important. While a common approach to achieve this is …
language has become increasingly important. While a common approach to achieve this is …
Control as probabilistic inference as an emergent communication mechanism in multi-agent reinforcement learning
This paper proposes a generative probabilistic model integrating emergent communication
and multi-agent reinforcement learning. The agents plan their actions by probabilistic …
and multi-agent reinforcement learning. The agents plan their actions by probabilistic …
A survey on emergent language
The field of emergent language represents a novel area of research within the domain of
artificial intelligence, particularly within the context of multi-agent reinforcement learning …
artificial intelligence, particularly within the context of multi-agent reinforcement learning …