| 1. |
- Andringa, Tjeerd C., et al.
(författare)
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Cognition from life : the two modes of cognition that underlie moral behavior
- 2015
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Ingår i: Frontiers in Psychology. - : Frontiers Media SA. - 1664-1078. ; 6
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Tidskriftsartikel (refereegranskat)abstract
- We argue that the capacity to live life to the benefit of self and others originates in the defining properties of life. These lead to two modes of cognition; the coping mode that is preoccupied with the satisfaction of pressing needs and the co-creation mode that aims at the realization of a world where pressing needs occur less frequently. We have used the Rule of Conservative Changes - stating that new functions can only scaffold on evolutionary older, yet highly stable functions - to predict that the interplay of these two modes define a number of core functions in psychology associated with moral behavior. We explore this prediction with five examples reflecting different theoretical approaches to human cognition and action selection. We conclude the paper with the observation that science is currently dominated by the coping mode and that the benefits of the co-creation mode may be necessary to generate realistic prospects for a modern synthesis in the sciences of the mind.
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| 2. |
- Botteldooren, Dick, et al.
(författare)
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From Sonic Environment to Soundscape
- 2015
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Ingår i: Soundscape and the Built Environment. - Boca Raton : CRC Press. - 9781482226317 - 9781482226324 ; , s. 17-41
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Bokkapitel (refereegranskat)
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| 3. |
- Niessen, Maria, et al.
(författare)
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Expectancy-Based Robot Localization Through Context Evaluation
- 2009
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Ingår i: Proceedings of the 2009 International Conference on Artificial Intelligence (ICAI 2009). - : CSREA Press. - 1601321090 ; , s. 371-377
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Konferensbidrag (refereegranskat)abstract
- Agents that operate in a real-world environmenthave to process an abundance of information, which maybe ambiguous or noisy. We present a method inspired bycognitive research that keeps track of sensory information,and interprets it with knowledge of the context. We test thismodel on visual information from the real-world environmentof a mobile robot in order to improve its self-localization.We use a topological map to represent the environment,which is an abstract representation of distinct places andthe connections between them. Expectancies of the placeof the robot on the map are combined with evidence fromobservations to reach the best prediction of the next place ofthe robot. These expectancies make a place prediction morerobust to ambiguous and noisy observations. Results of themodel operating on data gathered by a mobile robot confirmthat context evaluation improves localization compared to adata-driven model.
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