A systematic approach to answering the easy problems of consciousness based on an executable cognitive system
#consciousness #cognitive system #executable model #easy problems #computational approach #perception #attention #AI simulation
📌 Key Takeaways
- The article proposes a systematic method to address the 'easy problems' of consciousness using an executable cognitive system.
- It focuses on applying computational models to explain measurable aspects of consciousness, such as perception and attention.
- The approach emphasizes practical, testable frameworks over philosophical debates about subjective experience.
- This method aims to bridge cognitive science and artificial intelligence by creating functional simulations of conscious processes.
📖 Full Retelling
arXiv:2603.04440v1 Announce Type: cross
Abstract: Consciousness is the window of the brain and reflects many fundamental cognitive properties involving both computational and cognitive mechanisms. A collection of these properties was described as the "easy problems" by Chalmers, including the ability to discriminate, categorize, and react to stimuli; information integration; reportability; information access; attention; deliberate control; and the difference between wakefulness and sleep. These
🏷️ Themes
Cognitive Science, Artificial Intelligence
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--> Quantitative Biology > Neurons and Cognition arXiv:2603.04440 (q-bio) [Submitted on 20 Feb 2026] Title: A systematic approach to answering the easy problems of consciousness based on an executable cognitive system Authors: Qi Zhang View a PDF of the paper titled A systematic approach to answering the easy problems of consciousness based on an executable cognitive system, by Qi Zhang View PDF Abstract: Consciousness is the window of the brain and reflects many fundamental cognitive properties involving both computational and cognitive mechanisms. A collection of these properties was described as the "easy problems" by Chalmers, including the ability to discriminate, categorize, and react to stimuli; information integration information access deliberate control; and the difference between wakefulness and sleep. These "easy problems" have not been systematically addressed. This study presents a first attempt to address them systematically based on an executable cognitive system and its implemented computational mechanisms, built upon an understanding of conceptual knowledge proposed by Kant. The study suggests that the abilities to discriminate, categorize, react, report, and integrate information can all be derived from the system's learning mechanism; attention and deliberate control are goal-oriented and can be attributed to emotional states and its information-manipulation mechanism; and the difference between wakefulness and dream sleep lies mainly in the source of stimuli. The connections between the implemented mechanisms in the executive system and conclusions drawn from empirical findings are also discussed, and many of these discussions and conclusions are supported by demonstrations of the executive system. Comments: 21 pages, 2 figure, 3 tables Subjects: Neurons and Cognition (q-bio.NC) ; Artificial Intelligence (cs.AI); Emerging Technologies (cs.ET) Cite as: arXiv:2603.04440 [q-bio.NC] (or arXiv:2603.04440v1 [q-bio.NC] for this version) https://doi.org...
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