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Rivka Vizen. Goal Recognition. Master's Thesis, Hebrew University of Jerusalem,2023.
The human capacity to recognize another agent's plans and goals allows it to infer missing and future actions and predict the agent's goal. This ability constitutes a fundamental aspect of human social cognition. An in-depth understanding of these cognitive processes serves to identify impairments and promote advanced research in psychology. Additionally, it is relevant to engineering and artificial intelligence, as it can contribute to the development of algorithms for the recognition of goals and plans by computers. Contemporary algorithms for detecting agent intentions operate on the principle of rationality, assuming a predefined list of potential targets. To improve these algorithms to the level of human capacity that has dynamically formulated lists of goals, we need to understand the cognitive and visual attributes utilized by individuals in the goal-selection process. In this study, we propose that the Gestalt Laws serve as a foundational framework for comprehending visual perception's role in goal selection. To test the aforementioned hypothesis, a visual experiment was conducted. Participants were tasked with determining the appropriate placement of an object in space while being surrounded by other objects characterized by Gestalt Law features. We present the experiment's findings, revealing that Gestalt Law does indeed underlie the visual cognitive processes involved in goal selection. In addition, the data collected yields a wealth of information that can be leveraged for further research and exploration of unaddressed questions, such as potential priority distinctions between characteristics.
@mastersThesis{rivki-msc,
author = {Rivka Vizen},
title = {Goal Recognition},
school = {Hebrew University of Jerusalem},
year = {2023},
wwwnote = {},
abstract = {The human capacity to recognize another agent's plans and goals allows it to infer missing
and future actions and predict the agent's goal. This ability constitutes a fundamental
aspect of human social cognition. An in-depth understanding of these cognitive processes
serves to identify impairments and promote advanced research in psychology.
Additionally, it is relevant to engineering and artificial intelligence, as it can contribute to
the development of algorithms for the recognition of goals and plans by computers.
Contemporary algorithms for detecting agent intentions operate on the principle of
rationality, assuming a predefined list of potential targets. To improve these algorithms to
the level of human capacity that has dynamically formulated lists of goals, we need to
understand the cognitive and visual attributes utilized by individuals in the goal-selection
process. In this study, we propose that the Gestalt Laws serve as a foundational framework
for comprehending visual perception's role in goal selection.
To test the aforementioned hypothesis, a visual experiment was conducted. Participants
were tasked with determining the appropriate placement of an object in space while being
surrounded by other objects characterized by Gestalt Law features.
We present the experiment's findings, revealing that Gestalt Law does indeed underlie the
visual cognitive processes involved in goal selection. In addition, the data collected yields
a wealth of information that can be leveraged for further research and exploration of
unaddressed questions, such as potential priority distinctions between characteristics.
},
}
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