— Reinforcement learning (RL) is a learning control paradigm that provides well-understood algorithms with good convergence and consistency properties. Unfortunately, these algor...
Lucian Busoniu, Damien Ernst, Bart De Schutter, Ro...
The process of managing inconsistency is a fundamental activity that permeates a large part of the systems development process. Failure to identify inconsistencies may lead to maj...
: Partially-observable Markov decision processes provide a very general model for decision-theoretic planning problems, allowing the trade-offs between various courses of actions t...
Distributed Partially Observable Markov Decision Problems (POMDPs) are emerging as a popular approach for modeling multiagent teamwork where a group of agents work together to joi...
Decentralized control of a cooperative multi-agent system is the problem faced by multiple decision-makers that share a common set of objectives. The decision-makers may be robots...