Swarm robotics is an approach to collective robotics that takes inspiration from the self-
organized behaviors of social animals. Through simple rules and local interactions, swarm …

This article provides an overview of evolutionary robotics techniques applied to online
distributed evolution for robot collectives, namely, embodied evolution. It provides a …

Reinforcement learning (RL) has shown great success in increasingly complex single-agent
environments and two-player turn-based games. However, the real world contains multiple …

In the framework of fully cooperative multi-agent systems, independent (non-communicative)
agents that learn by reinforcement must overcome several difficulties to manage to …

At the turn of the century some cities and regions in Europe, Japan and the USA, displayed
an exceptional capacity to incubate and develop new knowledge and innovations. The …

Intelligent Cities and Globalisation of Innovation Networks combines concepts and theories
from the fields of urban development and planning, innovation management, and …

Conventionally, intelligence is seen as a property of individuals. However, it is also known to
be a property of collectives. Here, we broaden the idea of intelligence as a collective …

We consider the problem of designing (perhaps massively distributed) collectives of
computational processes to maximize a provided" world utility" function. We consider this …

Dynamic task allocation is an essential requirement for multi-robot systems operating in
unknown dynamic environments. It allows robots to change their behavior in response to …

In large multiagent games, partial observability, coordination, and credit assignment
persistently plague attempts to design good learning algorithms. We provide a simple and …