The pattern theory of self in artificial general intelligence: A theoretical framework for modeling self in biologically inspired cognitive architectures |
| |
| Affiliation: | 1. University of Nebraska at Omaha, Department of Philosophy, Arts and Sciences Hall Room 205, Omaha, NE 68182, USA;2. University of Memphis, Department of Philosophy, 337 Clement Hall, Memphis, TN 38152, USA;3. University of Memphis, Department of Computer Science, 375 Dunn Hall, Memphis, TN 38152, USA;4. University of Memphis, Institute for Intelligent Systems, 365 Innovation Drive, Suite 303, Memphis, TN 38152, USA;1. University of Campinas (UNICAMP), Campinas, SP, Brazil;2. RLAM Innovation Center, Ericsson Telecomunicações S.A., Indaiatuba, SP, Brazil;1. University of Illinois, Springfield, USA;2. Warsaw School of Economics, Poland;3. University of Rzeszów, Poland;1. Institute for Intelligent Systems Research and Innovation (IISRI), Deakin University, Waurn Ponds, VIC 3216, Australia;2. Kermanshah University of Technology, Kermanshah, Iran;3. Centre for Artificial Intelligence Research and Optimisation, Torrens University Australia, Fortitude Valley, Brisbane, 4006 QLD, Australia;4. Institute of Research and Development, Duy Tan University, Da Nang 550000, Viet Nam;5. Department of Statistics, Faculty of Science, Fasa University, Fasa, Fars, Iran |
| |
| Abstract: | In an attempt to provide a unified account for a vast literature discussing a multiplicity of selves, Gallagher (2013) has proposed a pattern theory of self. Subsequent discussion on this account has led to a concern that the pattern theory, as originally presented, stands as a mere list of aspects that fails to explain how they are related in real-time. We suggest that one way to address these criticisms, and further develop the pattern theory of self is by exploring how it can be used to aid research on self in artificial general intelligence, especially in the context of biologically inspired cognitive architectures. We furthermore propose a conceptual implementation for actualizing such research in regards to the LIDA (Learning Intelligent Decision Agent) cognitive model. |
| |
| Keywords: | Artificial general intelligence Self Biologically inspired cognitive architectures Global workspace theory Learning Intelligent Decision Agent (LIDA) |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
