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Author: Andrzej Bieszczad

Affiliation: California State University Channel Islands, United States

Keyword(s): Neural Network, Neurosolver, General Problem Solving, State Spaces, Search, Adversarial Search, Temporal Learning, Neural Modeling.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Enterprise Information Systems ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Learning Paradigms and Algorithms ; Methodologies and Methods ; Neural Based Data Mining and Complex Information Processing ; Neural Network Software and Applications ; Neural Networks ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Self-Organization and Emergence ; Sensor Networks ; Signal Processing ; Soft Computing ; Theory and Methods

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 a n adversarial game, to play it well it would need a good teacher. (More)

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

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

TY - CONF

JO - Proceedings of the 8th International Joint Conference on Computational Intelligence - 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

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