Behavior Selection Using Utility-Based Reinforcement Learning in Irregular Warfare Simulation Models
| Autor: | Christian J. Darken, Sotiris Papadopoulos, Jonathan K. Alt, Francisco Baez |
|---|---|
| Přispěvatelé: | Naval Postgraduate School (U.S.), Computer Science (CS) |
| Rok vydání: | 2013 |
| Předmět: |
Information Systems and Management
Computer Networks and Communications Computer science media_common.quotation_subject Population Agent-based social simulation Management Information Systems Agent Based Social Simulations Reinforcement learning Theory of Planned Behavior (TPB) education Commodity Consumption media_common education.field_of_study business.industry Theory of planned behavior Bayesian network Reinforcement Learning Computer Science Applications Variety (cybernetics) Computational Theory and Mathematics Conceptual model Artificial intelligence Adaptive learning Cultural Geography Model business Information Systems |
| Zdroj: | International Journal of Operations Research and Information Systems. 4:61-78 |
| ISSN: | 1947-9336 1947-9328 |
| DOI: | 10.4018/joris.2013070105 |
| Popis: | The article of record as published may be found at http://dx.doi.org/10.4018/joris.2013070105 The Theory of Planned Behavior (TPB) provides a conceptual model for use in assessing behavioral intentions of humans. Agent based social simulations seek to represent the behavior of individuals in societies in order to understand the impact of a variety of interventions on the population in a given area. Previous work has described the implementation of the TPB in agent based social simulation using Bayesian networks. This paper describes the implementation of the TPB using novel learning techniques related to reinforcement learning. This paper provides case study results from an agent based simulation for behavior related to commodity consumption. Initial results demonstrate behavior more closely related to observable human behavior. This work contributes to the body of knowledge on adaptive learning behavior in agent based simulations. |
| Databáze: | OpenAIRE |
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