Social learning is a key component of human and animal intelligence. By taking cues from
the behavior of experts in their environment, social learners can acquire sophisticated …

Intelligent human agents exist in a coop-erative social environment that facilitates learning.
They learn not only by trialand-error, but also through cooperation by sharing instantaneous …

The challenge of developing powerful and general Reinforcement Learning (RL) agents has
received increasing attention in recent years. Much of this effort has focused on the single …

We introduce MAgent, a platform to support research and development of many-agent
reinforcement learning. Unlike previous research platforms on single or multi-agent …

Observational learning is a type of learning that occurs as a function of observing, retaining
and possibly replicating or imitating the behaviour of another agent. It is a core mechanism …

We derive a new intrinsic social motivation for multi-agent reinforcement learning (MARL), in
which agents are rewarded for having causal influence over another agent's actions, where …

We propose a unified mechanism for achieving coordination and communication in Multi-
Agent Reinforcement Learning (MARL), through rewarding agents for having causal …

While recent work in reinforcement learning (RL) has led to agents capable of solving
increasingly complex tasks, the issue of high sample complexity is still a major concern. This …

Recent developments in reinforcement learning have been able to derive optimal policies
for sophisticated and capable agents, and shown to achieve human-level performance on a …

This article surveys reinforcement learning approaches in social robotics. Reinforcement
learning is a framework for decision-making problems in which an agent interacts through …