A navigation algorithm inspired by human navigation

Vijesh, M.; Iyengar, S. R. S.; Mahantesh, S. M. Vijay; Ramesh, A.; Pandurangan, C.; Madhavan, Veni

doi:10.1109/asonam.2012.225

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Cognitive Navigation and Its Thought Of Brain-inspired Reali...1

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Cited by 3 publications

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“…It has the potential to improve robustness, accuracy, real-time response, autonomous intelligence, and computational efficiency. Generally, it can be divided into brain-inspired spatial cognition layer and brain-inspired goal-directed navigation layer (Vijesh, M., et al, 2013).…”

Section: Cognitive Navigation and Its Thought Of Brain-inspired Reali...mentioning

confidence: 99%

Collision-avoidance navigation systems for Maritime Autonomous Surface Ships: A state of the art survey

et al. 2021

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Section: Cognitive Navigation and Its Thought Of Brain-inspired Reali...mentioning

confidence: 99%

Collision-avoidance navigation systems for Maritime Autonomous Surface Ships: A state of the art survey

et al. 2021

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Team Arrangement Heuristic Algorithm (TAHA): Theory and application

Babayan

Tahani

2019

Mathematics and Computers in Simulation

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Usertesting Without the User

Stahlke

Mirza-Babaei

2018

Comput. Entertain.

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The use of human participants in game evaluation can be costly, time-consuming, and present challenges for constructing representative player samples. These challenges may be overcome by using computer-controlled agents in place of human users for certain stages of the usertesting process. This article explores opportunities and challenges in the use of behavioural modelling to create independent “user” agents driven by artificial intelligence (AI). We highlight the utility of imitating cognitive processes such as spatial reasoning, memory, and goal-oriented decision-making as a means to increase the viability of independent agents as a tool in usertesting. Specifically, we investigate the possible design and use of proxy AI “users” that mimic human navigational behaviour to assist in the evaluation of level designs. Ultimately, we propose that a configurable population of AI players can provide a data-rich supplement to current approaches in games user research.

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A navigation algorithm inspired by human navigation

Cited by 3 publications

References 9 publications

Collision-avoidance navigation systems for Maritime Autonomous Surface Ships: A state of the art survey

Collision-avoidance navigation systems for Maritime Autonomous Surface Ships: A state of the art survey

Team Arrangement Heuristic Algorithm (TAHA): Theory and application

Usertesting Without the User

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