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Autonomous agents modelling other agents: A comprehensive survey and open problems
Much research in artificial intelligence is concerned with the development of autonomous
agents that can interact effectively with other agents. An important aspect of such agents is …
agents that can interact effectively with other agents. An important aspect of such agents is …
A survey of learning in multiagent environments: Dealing with non-stationarity
The key challenge in multiagent learning is learning a best response to the behaviour of
other agents, which may be non-stationary: if the other agents adapt their strategy as well …
other agents, which may be non-stationary: if the other agents adapt their strategy as well …
A survey of ad hoc teamwork research
Ad hoc teamwork is the research problem of designing agents that can collaborate with new
teammates without prior coordination. This survey makes a two-fold contribution: First, it …
teammates without prior coordination. This survey makes a two-fold contribution: First, it …
An efficient end-to-end training approach for zero-shot human-AI coordination
The goal of zero-shot human-AI coordination is to develop an agent that can collaborate with
humans without relying on human data. Prevailing two-stage population-based methods …
humans without relying on human data. Prevailing two-stage population-based methods …
The active inference approach to ecological perception: general information dynamics for natural and artificial embodied cognition
The emerging neurocomputational vision of humans as embodied, ecologically embedded,
social agents—who shape and are shaped by their environment—offers a golden …
social agents—who shape and are shaped by their environment—offers a golden …
Applying theory of mind to multi-agent systems: A systematic review
Life in society requires constant communication and coordination. These abilities are
efficiently achieved through sophisticated cognitive processes in which individuals are able …
efficiently achieved through sophisticated cognitive processes in which individuals are able …
Towards open ad hoc teamwork using graph-based policy learning
Ad hoc teamwork is the challenging problem of designing an autonomous agent which can
adapt quickly to collaborate with teammates without prior coordination mechanisms …
adapt quickly to collaborate with teammates without prior coordination mechanisms …
[PDF][PDF] A survey of ad hoc teamwork: Definitions, methods, and open problems
Ad hoc teamwork is the well-established research problem of designing agents that can
collaborate with new teammates without prior coordination. This survey makes a two-fold …
collaborate with new teammates without prior coordination. This survey makes a two-fold …
Reasoning about hypothetical agent behaviours and their parameters
Agents can achieve effective interaction with previously unknown other agents by
maintaining beliefs over a set of hypothetical behaviours, or types, that these agents may …
maintaining beliefs over a set of hypothetical behaviours, or types, that these agents may …
Deep interactive bayesian reinforcement learning via meta-learning
Agents that interact with other agents often do not know a priori what the other agents'
strategies are, but have to maximise their own online return while interacting with and …
strategies are, but have to maximise their own online return while interacting with and …