Market-Based Reinfor ement Learning in Partially Observable Worlds

On Using Guidan e in Relational Reinfor ement Learning

Fuzzy Model-Based Reinfor ement Learning

Kernel-Based Reinfor ement Learning

Market-Based Reinforcement Learning in Partially Observable Worlds

Unlike traditional reinforcement learning (RL), market-based RL is in principle applicable to worlds described by partially observable Markov Decision Processes (POMDPs), where an agent needs to learn short-term memories of relevant previous events in order to execute optimal actions. Most previous work, however, has focused on reactive settings (MDPs) instead of POMDPs. Here we reimplement a r...

Algorithms for Inverse Reinfor ement Learning