As the reach of multiagent reinforcement learning extends to more and more complex tasks, it is likely that the diverse challenges posed by some of these tasks can only be address...
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Multi-agent teamwork is critical in a large number of agent applications, including training, education, virtual enterprises and collective robotics. Tools that can help humans an...
Modern interactive computer games provide the ability to objectively record complex human behavior, offering a variety of interesting challenges to the pattern-recognition communi...
Bernard Gorman, Christian Bauckhage, Christian Thu...