A Projective Simulation Scheme for Partially-Observable Multi-Agent Systems

Abstract

We introduce a kind of partial observability to the projective simulation (PS) learning method. It is done by adding a belief projection operator and an observability parameter to the original framework of the efficiency of the PS model. I provide theoretical formulations, network representations, and situated scenarios derived from the invasion toy problem as a starting point for some multi-agent PS models.

arXiv comment28 pages, 21 figures

References in corpus (11)

• Quantum Machine Learning
• Quantum strategies
• Active learning machine learns to create new quantum experiments
• Quantum speedup for active learning agents
• Machine learning for long-distance quantum communication
• Distribution of entanglement in large-scale quantum networks
• Adaptive quantum computation in changing environments using projective simulation
• Projective simulation for classical learning agents: a comprehensive investigation
• Projective simulation with generalization
• Meta-learning within Projective Simulation
• Quantum machine learning with glow for episodic tasks and decision games