|
|||||
|
|
Learning algorithm for an intelligent decision making system based on multi-agent neurocognitive architectures |
|
| Affiliation: | 1. National Research Nuclear University “Moscow Engineering Physics Institute”, Moscow 115409, Russian Federation;2. NAO “JurInfoR”, Moscow 119435, Russian Federation;1. Laboratoire de Psychologie des Pays de la Loire (LPPL-EA 4638), Nantes Université, Univ Angers, Nantes, France;2. Unité de Gériatrie, Centre Hospitalier de Tourcoing, Tourcoing, France;3. Institut Universitaire de France, Paris, France;4. School of Psychology, Western Sydney University, Sydney, NSW, Australia;5. MARCS Institute for Brain and Behaviour, Western Sydney University, Sydney, NSW, Australia;6. Department of Human Anatomy and Physiology, The Faculty of Health Sciences, University of Johannesburg, Johannesburg, South Africa |
| Abstract: | The paper presents the formalism of an intelligent decision-making system based on multi-agent neurocognitive architectures, which has an architectural similarity to the human brain. An invariant of the organizational and functional structure of the intellectual decision-making process based on the multi-agent neurocognitive architecture is developed. An algorithm for teaching intelligent decision-making systems based on the self-organization of the invariant of multi-agent neurocognitive architectures is presented. Using this algorithm, an intelligent agent was trained and the architecture of the learning process was built on the basis of an invariant of neurocognitive architecture. Further research is related to training an intelligent agent in more complex behavior and expanding the capabilities of an intelligent decision-making system based on multi-agent neurocognitive architectures. |
| Keywords: | Multi-agent systems Neurocognitive architecture Decision making Artificial intelligence systems Reasoning models Intelligent agents |
| 本文献已被 ScienceDirect 等数据库收录！ | |