
Comparative Evaluation of MultiAgent Deep Reinforcement Learning Algorithms
Multiagent deep reinforcement learning (MARL) suffers from a lack of co...
read it

An Empirical Study on the Practical Impact of Prior Beliefs over Policy Types
Many multiagent applications require an agent to learn quickly how to in...
read it

Comparative Evaluation of Multiagent Learning Algorithms in a Diverse Set of Ad Hoc Team Problems
This paper is concerned with evaluating different multiagent learning (M...
read it

Exploiting Causality for Selective Belief Filtering in Dynamic Bayesian Networks (Extended Abstract)
Dynamic Bayesian networks (DBNs) are a general model for stochastic proc...
read it

Are You Doing What I Think You Are Doing? Criticising Uncertain Agent Models
The key for effective interaction in many multiagent applications is to ...
read it

EHBA: Using Action Policies for Expert Advice and Agent Typification
Past research has studied two approaches to utilise predefined policy se...
read it

Belief and Truth in Hypothesised Behaviours
There is a long history in game theory on the topic of Bayesian or "rati...
read it

A GameTheoretic Model and BestResponse Learning Method for Ad Hoc Coordination in Multiagent Systems
The ad hoc coordination problem is to design an autonomous agent which i...
read it

Exploiting Causality for Selective Belief Filtering in Dynamic Bayesian Networks
Dynamic Bayesian networks (DBNs) are a general model for stochastic proc...
read it

Autonomous Agents Modelling Other Agents: A Comprehensive Survey and Open Problems
Much research in artificial intelligence is concerned with the developme...
read it

Reasoning about Unforeseen Possibilities During Policy Learning
Methods for learning optimal policies in autonomous agents often assume ...
read it

Stabilizing Generative Adversarial Network Training: A Survey
Generative Adversarial Networks (GANs) are a type of Generative Models, ...
read it

Dealing with NonStationarity in MultiAgent Deep Reinforcement Learning
Recent developments in deep reinforcement learning are concerned with cr...
read it

Reasoning about Hypothetical Agent Behaviours and their Parameters
Agents can achieve effective interaction with previously unknown other a...
read it

On Convergence and Optimality of BestResponse Learning with Policy Types in Multiagent Systems
While many multiagent algorithms are designed for homogeneous systems (i...
read it

Variational Autoencoders for Opponent Modeling in MultiAgent Systems
Multiagent systems exhibit complex behaviors that emanate from the inte...
read it

Integrating Planning and Interpretable Goal Recognition for Autonomous Driving
The ability to predict the intentions and driving trajectories of other ...
read it

A TwoStage Optimization Approach to SafebyDesign Planning for Autonomous Driving
Lessons learned from the increasing diversity of road trial deployments ...
read it

Open Ad Hoc Teamwork using Graphbased Policy Learning
Ad hoc teamwork is the challenging problem of designing an autonomous ag...
read it

Opponent Modelling with Local Information Variational Autoencoders
Modelling the behaviours of other agents (opponents) is essential for un...
read it

Shared Experience ActorCritic for MultiAgent Reinforcement Learning
Exploration in multiagent reinforcement learning is a challenging probl...
read it
Stefano V. Albrecht
is this you? claim profile