---
abstract: 'We introduce a kind of partial observability to the projective simulation (PS) learning method via Dirac notation. It is done by adding a projection operator and an observability parameter to the original formulation of the efficiency in PS model. Our examples are from invasion toy problem regarding a multi-agent setting.'
author:
- 'R. Kheiri'
date: 'Received: date / Accepted: date'
title: 'A Projective Simulation Scheme for a Partially-Observable Multi-Agent Game '
---

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Introduction {#intro}
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Projective simulation, to put it briefly, is an embodied learning method which tries to represent a reductionist approach of a brain-like learning (thinking) scheme utilizing random walks between some network of clips via their interface edges as episodic and compositional memories. In the article titled “projective simulation for artificial intelligence” [@Briegel1], the authors formulate PS model using a toy problem as “invasion game” and checked the speed of learning, maximum blocking efficiency, etc. from which we expand our examples on it for the early step of introducing the partially observable PS method.

As the primary feature, the PS 