Exploring the Neurosolver in Playing Adversarial Games

Andrzej Bieszczad

2016

Abstract

In the past, the Neurosolver, a neuromorphic planner and a general problem solver, was used in several exploratory applications, such as Blocks World and Towers of Hanoi puzzles, that in which we investigated its problem solving capabilities. In all of them, there was only one agent that had a single point of view focus: how to solve a posed problem by generating a sequence of actions to get the system from its current state to some goal state. In this paper, we report on our experiments with exploring the Neurosolver’s capabilities to deal with more sophisticated challenges in solving problems. For that purpose, we employed the Neurosolver as a driver for adversary games. In that kind of environment, the Neurosolver cannot just generate a plan and then follow it through. Instead, the plan has to be revised dynamically step by step in response to the other actors following their own plans realizing adversarial points of view. We conclude that while the Neurosolver can learn to play an adversarial game, to play it well it would need a good teacher.

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Paper Citation


in Harvard Style

Bieszczad A. (2016). Exploring the Neurosolver in Playing Adversarial Games . In Proceedings of the 8th International Joint Conference on Computational Intelligence - Volume 3: NCTA, (IJCCI 2016) ISBN 978-989-758-201-1, pages 83-90. DOI: 10.5220/0006070800830090


in Bibtex Style

@conference{ncta16,
author={Andrzej Bieszczad},
title={Exploring the Neurosolver in Playing Adversarial Games},
booktitle={Proceedings of the 8th International Joint Conference on Computational Intelligence - Volume 3: NCTA, (IJCCI 2016)},
year={2016},
pages={83-90},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006070800830090},
isbn={978-989-758-201-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 8th International Joint Conference on Computational Intelligence - Volume 3: NCTA, (IJCCI 2016)
TI - Exploring the Neurosolver in Playing Adversarial Games
SN - 978-989-758-201-1
AU - Bieszczad A.
PY - 2016
SP - 83
EP - 90
DO - 10.5220/0006070800830090