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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Schneider, M. Adamy, J. |
| Copyright Year | 2015 |
| Description | Author affiliation: Lab. of Control Methods & Robot., Tech. Univ. Darmstadt, Darmstadt, Germany (Schneider, M.; Adamy, J.) |
| Abstract | Motivation and emotion are inseparable component factors of value systems in living beings, which enable them to act purposefully in a partially unknown and sometimes unforgiving environment. Value systems that drive innate reinforcement learning mechanisms have been identified as key factors in self-directed control and autonomous development towards higher intelligence and seem crucial in the development of a concept of “self” in sentient beings [1]. This contribution is concerned with the relationship between artificial learning control systems and innate value systems. In particular, we adapt the state-of-the-art model of motivational processes based on reduction of generalized drives towards higher flexibility, expressivity and representation capability. A framework for modelling self-adaptive value systems, which develop autonomously starting from an inherited (or designed) innate representation, within a learning control system architecture is formulated. We discuss the relationship of anticipated effects in this control architecture with psychological theory on motivations and contrast our framework with related approaches. |
| Starting Page | 1 |
| Ending Page | 8 |
| File Size | 306599 |
| Page Count | 8 |
| File Format | |
| ISSN | 21614407 |
| e-ISBN | 9781479919604 |
| DOI | 10.1109/IJCNN.2015.7280623 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-07-12 |
| Publisher Place | Ireland |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Biology Artificial intelligence Cognition Adaptation models |
| Content Type | Text |
| Resource Type | Article |
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